Health
Ep 347 - New Retraction (and What It Means For "Evidence-Based" Fitness)
In this episode of Iron Culture, Eric Trexler delves into the recent retraction of a controversial study on apple cider vinegar as a weight loss aid. He discusses the implications of this retraction f...
Ep 347 - New Retraction (and What It Means For "Evidence-Based" Fitness)
Health •
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Interactive Transcript
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Hello everybody welcome back to Iron Culture. It is me, Eric Trexler, alone, afraid and
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alone. It's just going to be me this episode. Helms is off doing whatever it is. Helms
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does, who can say. So I'm holding down the fort here. I already have extremely negative
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chatter in the live chat. We've got Expanda asking where is my jazz music. That was one of
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the best things about the podcast being the live jazz music. I tell you what, Expanda,
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since you were the first person in the live chat here over on the Iron Culture YouTube
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channel, I'm going to commit to you. I will bring back the intro music. I've made many
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mistakes in my life. One of them was veering away from that music intro. I am on it. I will
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make it happen. So folks, as you are settling into the live chat, once again welcome to the
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show. This is going to be a little bit different of an episode. What I'm going to do today is
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take you through a recent happening in the world of evidence-based fitness slash nutrition
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stuff. It was a really interesting back and forth, a really interesting saga, I guess you
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would say, that took almost two years to kind of happen. So I want to walk through what went down
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and more importantly after that, what it kind of tells us about the state of science in the
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world of exercise and nutrition and kind of what it means in terms of how we might move
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forward in attempt to be someone who is evidence-based. There's all these content creators who make
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kind of quote-unquote evidence-based fitness content. A lot of people claim to be science-based
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lifters or take a science-based approach to their nutrition. I think in order for any of those
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who really carry any weight or mean anything, it means very seriously and rigorously engaging
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with the evidence and the research that exists and also being critical of that where it's warranted,
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not only the research itself, but also the processes that are intended to maintain the integrity
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of that research. So we're going to talk about an interesting saga where basically this paper was
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published about apple cider vinegar as a weight loss tool. Almost immediately it caught my eye,
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teamed up with a couple fantastic people. I'll talk about as we go here. We wrote a letter to
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the editor and the whole thing kind of snowballed from there. And just within the last week or so,
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that paper was actually retracted. And so we're going to talk through how that process went down
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the investigation that unfolded what the investigation found. And then again, talking big picture,
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what does this mean for people who regularly try to translate evidence into practice?
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But before we get into that, a couple things to get out of the way here. If you enjoy the show and
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you want to support it, there's many ways to do it. Make sure that you like, make sure that you
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rate, make sure you subscribe. You know all the good stuff. Leave a review if you like the show.
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If you don't like the show, maybe don't leave a review. Maybe skip that part. But do make sure
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that you're subscribed. And of course, if you want to be a massive top tier ultra supporter,
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make sure you head over to massresearchreview.com and consider becoming a member of the mass
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community. We put out a research review the first of the month. Every single month we've been doing
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it since 2017. So we've got a new issue coming out in just a couple days here on October first.
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And it is a doozy. Here's my sales pitch. If you were a member of the mass community,
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then you knew about this apple cider vinegar paper essentially as soon as it came out. And you
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probably did not take it particularly seriously. And you certainly, if you're a member of the mass
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community, did not actually act upon the information in it. So if you want to be approximately two
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years ahead of the research curve, become a member of the mass community. One other thing I want to
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mention, I want to give a shout out to our dear friends at Elite FTS. If you have any needs
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related to gear or apparel of the lifting variety, make sure you head over to EliteFTS.com.
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You can use our discount code MRR10. It stands for massresearchreview10 to get 10% off most items
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in their online store. Elite FTS, if you don't know, it's Dave Tates operation over there in
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central Ohio. They have been a fixture in the iron game for a very long time making extremely
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high quality products. And as we've talked about in previous episodes, I've been using stuff
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from EliteFTS since about, I don't even have access to the email that I would have used to
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to look up my order confirmation. I think that I've been using their stuff since like 2010,
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maybe, wrist wraps, straps, you name it. So if you're in the market for any of, you know,
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your lifting related stuff, bands, I'm sure they've got all sorts of knee wraps and sleeves and
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you name it, I'm sure they've got it over there. So head over to EliteFTS.com, use the code MRR10.
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All right, folks, let's go ahead and dive in here. As I mentioned, it was a couple years ago,
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almost, that this paper came across my desk. It was called Apple Cider Vinegar for weight management
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and Lebanese adolescents and young adults with overweight and obesity, a randomized double-blind
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placebo controlled study. And this paper, in short, really caught my attention. It was published in
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BMJ Nutrition Prevention and Health. And the easiest way to summarize the findings in a nut shell
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is this paper came out and reported very substantial fat loss effects. Whether you're talking
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about the change in fat mass or the change in BMI or the change in body weight, the effects were
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very, very striking for a relatively short-term intervention. And basically, we crunch the numbers.
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And the effects of Apple Cider Vinegar in terms of weight loss were comparable. And in some
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cases, depending on what trial you're looking at, better than the effects of ozempic on weight loss.
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And so that's going to catch my eye 10 times out of 10. Because if you tell me that I can take 5 or
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10 or 15 milliliters of Apple Cider Vinegar a day, and that's going to give me ozempic-like
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results without ozempic-like potential side effects. Now, I'm not a person who bashes
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these GLP-1 weight loss drugs. I actually think they're quite a marvel, pretty incredible
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as it, you know, as, you know, new medications go. I've been really amazed by, you know,
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what we've seen in that space in terms of the research and the clinical applications. But,
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nonetheless, they do, of course, like any other medication have a side effect profile. Some of
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those side effects, although rare, can be substantial. So if you tell me, hey, we've got this thing,
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it works as well. The side effects are not nearly as, you know, even though the low probability
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ones are not nearly as severe. And also, you know, if that's true, then we could instead of having
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this giant, like, $100 billion industry or whatever it's at these days, we can just use Vinegar.
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So, for example, the last time I looked into the actual pricing for what it would take to be on
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like a GLP-1 drug, I saw various things, but, you know, over the last couple of years,
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depending on when you looked, it might be somewhere in the ballpark of 500 or even up to $1,000 a month.
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And so, you know, basically, the value proposition is, what if I gave you this Apple cider vinegar,
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and instead of 500 to $1,000 a month, we're talking about, like, I don't know, $6 a month,
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I haven't priced out, haven't priced out vinegar lately, but a fundamentally negligible cost
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with a lower side effect profile. Not only is that a huge game changer, if true, at the personal
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level, but it also essentially wipes out an enormous, what has essentially become a sub-industry
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of the pharmaceutical industry. So, it was very surprising to me and to my colleagues that nobody
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was looking at this with the level of skepticism and scrutiny and saying, why are we still doing
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ozemic and similar GLP-1 drugs if we are to take this seriously? And I've never gotten a good answer
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for that. Again, under the assumption that we're taking the findings seriously and literally.
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So, again, we crunch the numbers and basically what we found is in terms of weight loss,
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as reported, we were looking at something that was similar, if not in some cases,
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better than ozemic for weight loss. And essentially, there's two levers you could pull mechanistically
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to make that happen. One would be a reduction in energy intake that, again, rivals what we see with
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these potent GLP-1 drugs. The other potential mechanism was, well, maybe this is increasing energy
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expenditure by far a less probable mechanism. But if so, if you actually crunch out the numbers,
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then essentially what we're looking at is something that is increasing energy expenditure
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at rest to a level that we haven't seen since looking at DNP. And the problem with DNP is that
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sometimes it literally kills people if they take too much because of this dangerous increase in
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energy expenditure. So DNP is what they call an un-coupling agent as it pertains to proton leak
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within the mitochondria. And so what that means is basically it causes extra proton leakage
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within the mitochondria, which decouples that flux of protons from the actual process of generating ATP.
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So under normal circumstances, that whole process is linked and the movement of those protons
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within the mitochondria ultimately facilitates the production of ATP. But if there's leakage,
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if there's excess leakage, then what happens is your body is kind of going through and doing
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metabolism. It's doing all the preliminary steps, including the stuff that actually increases
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thermogenesis. So as a byproduct of just doing metabolism to create ATP, our body burns calories
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and generates heat. But the payoff is supposed to be at the last step, we generate all this ATP
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to fuel body functions. And so therefore, there's this really nice feedback loop where we burn these
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calories. We increase this, you know, we have this thermogenic effect where we're generating heat.
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But because we're creating ATP, then we stop doing so much metabolism because we say,
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cool, we've got all the ATP we're trying to create. Now we can chill a little bit. But if you have
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all this extra proton leak, then you're going through all the calorie burning and the heat generation,
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but you're not generating as much ATP. And so therefore, you do, as I'm used to talking in a cadence to
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inspire my students to shout out or participate, but I don't hear anyone shouting into my headphones
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right now. But basically, you know, if you are doing this whole process, these protons are leaking,
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you're not creating all that ATP, you're going to do more metabolism. And so you're churning through
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even more calories, generating even more heat. And so what we find is when people take, especially
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very high doses of DNP, there's this kind of runaway metabolism that causes this massive
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expenditure of calories, but more problematically, this massive increase in metabolic heat generation.
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And in some cases, there have been situations where that kind of runaway metabolism and heat
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generation has led to fatal instances of hyperthermia, even in thermonutral conditions. So people that
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are just sitting in a normal temperature room who are doing metabolism at such a rate and without a
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functioning feedback loop, such that they generate a tremendous amount of body heat and ultimately die.
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So that is kind of the premise of why we had the initial premise of why there was so much scrutiny
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and skepticism of this paper is, what are you telling me? Are you telling me that this reduces appetite
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on the level of ozemic or that it increases expenditure on the dangerous level of DNP? And also,
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side effects reported or if they're where they were extremely minor in nature. So
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yeah, there were just things that in terms of face validity just didn't seem to make much sense.
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So that leads to a letter to the editor teamed up with VaHeed Malbooby. I could be mispronouncing
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his name. We've emailed a million times, but I don't think we've actually chatted or I've certainly
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never heard his name spoken in the course of conversation, but VaHeed is the lead author.
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And of course, we teamed up with none other than the James Hethers, who has really
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carved out a bit of a niche in this space of identifying research for which there is great skepticism
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and ultimately shining the light on that research. In some cases, it may be warranted to follow
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up with an investigation. In some cases, James's work has led to retractions of papers. So
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James is a seasoned veteran in this pursuit of following up on papers that lead to tremendous
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skepticism and getting to the root of what might be causing the findings that have been observed.
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So we basically wrote this letter to the editor. It is published on BMJ nutrition prevention and
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health where we talk about a variety of things. We talk about the magnitude of effects, which
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certainly caught our eye and raised concerns about biological plausibility in terms of identifying
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a mechanism that could actually make that happen and not be dangerous. We talked about some data
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characteristics using a procedure called sprite that gave us some cause for concern in terms of
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just the way the data were reported. So we presented some graphs saying, you know, if these
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data in these tables are what they say they are, then these must be some very unusual data
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distributions that are hiding in the actual data set. And our question was, how would the data
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come to be distributed that way? It would be very much statistical improbability if not a statistical
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anomaly in some cases. Of course, we talked about some issues we had with the actual statistical
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approach that was taken. And again, at the end kind of laid out, you know, our concerns about if
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we compare these effects against things like GLP1 drugs and DNP or 2, 4, dyneitrophenol, things just
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don't seem to be adding up here. And you know, the final thing that we kind of mentioned or alluded
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to in this letter is in the original paper, the authors basically had a data disclosure statement
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at the end of it that said, all the data for this study have been uploaded as a supplementary file.
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And so when I first read this paper, I thought, cool, I'm going to dive into the supplementary file
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and get to the bottom of resolving all of my concern, skepticism, etc. If they uploaded the data,
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then I'll just take a look and see why these table values look the way they do.
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But when you go to the supplementary file or when you did originally, when the paper was published,
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it would just take you to a press release by the journal, which was basically just hyping up the
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paper itself. And so that is not actually technically data to include a press release that
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just hypes up the findings. So we also included that. We said, hey, all of our concerns could be
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alleviated if we could just take a peek at the data, which was allegedly supposed to be made available.
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So if you could make that available, that would sure be terrific. And then of course, before we
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wrote this, I should mention we emailed the corresponding author of the paper multiple times asking for
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the data set, which took as far as we could tell was by accident, essentially not uploaded with
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the original paper. And so we're just like, hey, it says it's uploaded as a supplementary file.
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If you could send us the data, we'd love to take a look at it. And none of our emails, we tried
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multiple times. None of them were eventually answered. So that led to this process of, so
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I'm going to go through the timeline in a bit. But let's pretend that time went in a linear
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fashion here. So we published the letter to the editor. And then eventually there was a response.
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And to be totally honest, the response to the letter annoyed me more than the original paper.
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So basically they kind of went through and almost addressed some of our concerns, but not really.
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So for the statistical methodology, they basically defended using T tests instead of analysis of
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variants with no adjustment for multiplicity, which without getting too technical, basically
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that perspective lives in a world or some kind of alternate universe where we didn't decide in
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about the 1930s. It's been nearly a hundred years since we decided that's probably not a good idea.
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And we should probably at the bare minimum do some kind of multiplicity adjustment.
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Of course, with this particular study, it goes beyond that. It should have also included a baseline
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a baseline adjustment, some type of ANCOVA type approach or linear mixed model that has a
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baseline adjustment. There were a lot of opportunities to do a better approach statistically that is
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frankly more valid. And they just kind of said, no, we're not going to do any of that. No thank you.
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For the biological plausibility, they basically said like there's evidence that apple cider vinegar
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can significantly influence body weight, fat mass, and metabolic markers such as blood glucose,
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insulin sensitivity, and triglyceride levels. They mentioned that the acetic acid component can
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enhance fat oxidation or inhibit fat synthesis by increasing mitochondrial activity. But again,
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none of this really makes any sense when you apply it to the kind of magnitude effect that we're
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talking about. So if you're talking about without impacting energy expenditure, promoting fat
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oxidation, well then, okay, we might see a modest increase in fat oxidation at the expense of
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carbohydrate or protein oxidation. But we're in the world at all these calories go. That is not
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something that would be answered by that kind of mechanistic justification. They took issue with
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our use of the sprite analysis and said these kinds of reconstruction techniques in their words are
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sensitive to assumptions and should not be viewed as definitive evidence of data irregularities.
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In fact, data simulation models often result in variations that may not necessarily mirror the
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original data set, which is interesting because if we highlight like hey, these data distributions
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look odd. The easiest way to rebut that type of comment is to simply plot the data distributions and
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say nope, here they are. They are not odd. They are very normal. They are very typical. And so that
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did not happen. And so it was basically like, their response was like, have you ever considered that
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you might be wrong without giving any evidence to make us believe that we were wrong.
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Data availability, they basically said like, well, this is more of like an ethics and privacy thing,
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which I would be open to if the original paper didn't say we are happy to upload our data. Here
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it is attached to this submission. So if from the jump, they basically said hey, our university is
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really particular about this stuff for liability reasons. And therefore they're very particular about
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how, how, when, where, and why we make data available. I could live with that on the initial
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initial submission to the journal. But if you tell me, hey, it's just attached. Make sure you
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download it. And then you say, no, I'm definitely not going to let you see it. To me, that's a bit
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of a problem. And so I think one of the things that made me really annoyed about, about this
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particular letter is like, so for example, you see here this paper by Daniel Lackins. This was
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just egregiously misscited. They basically cited it while making a claim that is not at all
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supported by the paper itself. So that to me was very annoying because it's just like, here's
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a statement that is not true and not in this paper. But we're going to cite this paper. The reason
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that gets under my skin is because it's a great paper. I have like a personal level, like fondness
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for this paper. And to see it misused in that way was particularly grating to me. And then,
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just making statements that don't hold water whatsoever statistically. It's one thing to
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misscite that paper. And also the other thing that drove me nuts was we're just pretending that
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we don't need any kind of post-hoc corrections for multiple T-tests, which again, that was old news
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in 1941. So unless you're going to substantially rewrite the last nine decades of statistical
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literature, you kind of have to give me more than like, what if I didn't adhere to like basic
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best practices? So it bothered me that this letter was written, but it bothered me way more that it
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was accepted. And so when this was accepted, I wrote a letter, not a letter, I wrote an email saying
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like, what in the world are we doing here? But I think, oh, my light went off on me. There we go.
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I think my dear friend, James Heather's, wrote a very funny blog post over on his
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substack. It's called JamesClaims.substack.com. And he kind of walks through
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how this all went down. And I love the way that he laid out the timeline. Because I said previously,
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like for the time being in the interest of just being concise, we'll pretend that time advanced
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in a linear way. But I can promise you, this stuff all happened super out of order in a very
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strange way. So as James recounts it in May, 2024, he sees this paper in the way he said, the way
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he puts it, it was full of unlikely features, contradictory data and generalized silliness.
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The good way to put it. So then, you know, me and the heed have been kind of talking about this
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paper. We see that he's talking about this paper. We kind of team up and decide, let's,
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let's do this the right way. The right way to do this is first, you email the corresponding author
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for the data, that is procedurally the correct thing to do. And with multiple attempts and ample
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time, if you never hear a response, then you write a letter to the editor and you let the journal
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handle it. So the, like I said, the paper was published in May. We sent them the letter to the
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editor in June. And it was published in October. Or I'm sorry, it was accepted in October.
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Now, in November or December of 2024, I forget which one, that was when they published their
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rebuttal to our letter to the editor. But major issue, our correspondent, our letter to the editor
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was not published. So basically, the journal published their response to our letter to the editor,
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which to readers did not exist. So they didn't cite our letter to the editor. And they were basically
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arguing with ghosts. They were, they were arguing against a thing that in the eye of the reader
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did not exist and could not be accessed. So then we told the journal, like, hey, you, you kind of
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have to like publish our letter as well. So people can see what's going on here. What was really
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crazy about it, James lays out the timeline numerically. And so basically, this paper got retracted
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559 days after it was published, 504 days after James first published his criticisms, 464 days,
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after we submitted our letter to them. And what's really weird and was annoying was that at first,
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they were going to charge us over $2,600 US dollars to submit that letter to the editor,
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which I don't think people know how this works. But like, with open access journals,
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you have to pay to publish your paper, which is a whole conversation unto itself that I could
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gripe about forever. But what was particularly crazy about that was we were annoyed because this
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paper got published in our view shouldn't have. We didn't think it received a proper and appropriate
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level of scrutiny in the peer review process. So now we're going through the trouble of writing,
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you know, compiling this evidence, doing these analyses to inform the journal, like, hey, for your
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sake, to the extent you value your reputation, you should act upon this. And at first, like, I had
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to work really hard to get them to not charge us $2,600, 20, 26, 52 for doing what they should have
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done at the beginning for them, which was just extremely annoying. So I think James went back
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and counted. And by his count, I'll take his word for it. There were 12 emails back and forth to
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try to figure out whether or not we should have to pay $2,600 to correct what they had mistakenly
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done. James estimates that this process took approximately 100 emails in total. Zero is,
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by the time they retracted it, they actually didn't tell us first. They just did it. And then I
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think like two days later, I finally got an email saying, oh, by the way, thanks for sending 100
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emails back and forth. We decided to retract that a few days ago. So I kind of buried the lead,
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but eventually at the end of the day, we submitted this original letter to the editor.
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There was all the shenanigans about for some reason it was accepted but not published. And then
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they responded with this letter to the ghost remnants of what our letter was. Then eventually, they
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got our letter up. But all of this essentially plus the emails that I sent after this rebuttal to
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our letter where I was like, none of these claims are appropriate and some of them are just flat
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wrong. Basically, none of them were sufficient and some of them were just flatly not true.
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Basically, what they did was initiate some kind of statistical
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investigation that we were not a part of. I have no idea who did that, the investigation itself.
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So after that investigation on the 23rd of September, they go ahead and submit this
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retraction. And in the supplementary material, that's where I got a few laughs because they
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uplet up. They included a supplementary file that kind of talks through how they did this,
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like they did a very formal write up that whoever did the statistical review of what they did
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and what they found. And going through that, I got some serious kicks out of that. Because at the
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end of the day, we essentially claimed in our letter we're like, hey, these data distributions look
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really weird if you reconstruct what they would be based on the summary data that we're seeing in
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these tables. And then in their rebuttal, they were just like, no, sometimes people mess up when
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they try to reconstruct this stuff and you're making assumptions and stuff like that. So just
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leave it alone, basically what it came down to. So according to the statistical review,
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they looked at the results reported in table three of the article. This was the anthropometric
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outcomes, some of the key variables. And they said of the 128 values reported in table three,
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none of them agreed with the supplied data set. So the researchers gave these statisticians a
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data set that general basically made them the statisticians tried to reconstruct the tables in
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the paper. And they went zero out of 128. We're trying to reconstruct the values in table three.
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For table four, there were 128 values in table four. And they went zero out of 128 for trying to
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reconstruct those values. So to me, that makes it all the more rich that in the rebuttal to our
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letter that basically said, like, hey, we have some concerns about like what these data must look
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like based on the summary data in these tables. Basically, the outcome is, yeah, well, that's because
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none of the values in the tables actually match the underlying data sheet. So it turns out that
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the assumption driven reconstructions that we tried actually had some veracity. And indeed,
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there was more to get to the bottom of in terms of why those table values look so odd. It turns out
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they were not reflective of the data, which is an interesting turn of events. So I'm not going to get
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too much further into the weeds. All this stuff is documented. You can read about it if you like.
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But I think James did a great job kind of writing about how annoying this whole process was,
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how long it took. And the last thing that I want to highlight is one of the reasons that this
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matters so much. I can't really see at one point in time, I remember checking and seeing that even
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though this was a fairly new paper when I checked, it was, I believe, the most red paper in the
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history of this journal, which means it just caught on like wildfire and was immediately kind of
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circulating and making the rounds. So there's something called alt metrics, which basically seeks to
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quantify how much a research paper gets shared posted on the internet commented about things like
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that. And so the alt metric, basically, if an alt metric value is high, basically means this thing
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went viral. People saw it, people talked about it, people were interested in it. And at the end of
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the day, that means essentially it had a big impact. It got to a lot of people who saw here are the
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findings of a peer reviewed paper. And in theory, this is science. This is what you can take to the
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bank and believe and apply. So when you look at the alt metrics, the details here say this paper was
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in the top 5% of all research outputs scored by this alt metric system. So of all research, we're
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talking about top 5% tile. It says this is one of the highest scoring outputs from this source.
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It says this had a high attention score compared to outputs of the same age, put it in the 99th
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percent tile, basically meaning among newer studies, this thing really caught fire and lit pretty viral.
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And so it was mentioned by 193 news outlets. And you know, all down the list, this got a lot of
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attention and was shared widely. Not, and I don't care about the clicks, I care about the message.
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Right. This paper was shared broadly as scientific evidence for what you ought to do.
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And the reason that I bring up those numbers is I've written a previously I wrote a mass article
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where I basically said that retractions aren't enough. Basically, retractions don't work in the way
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we hope for them to work. And basically what I meant by that was, you know, there's all these
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paper. I think I was writing specifically in the context of a really widely read paper about,
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it was about ice baths, right. And so there's this paper about ice baths. It got spread all over
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and people were reading it like crazy. It was wildly popular and eventually got retracted because
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it was rubbish. But it got retracted after it reached like millions and millions and millions of
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people. I think at one point I tabulated that the results were out there conveyed as scientific
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truth to I think I estimated about five six million people. And so then you publish this little
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retraction notice and like 15,000 people hear about it. And so it's like, well, six million people
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heard this was true. And then 15,000 said, actually, a year later, never mind, forget about all that.
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There are so many people impacted by these findings who hear them, accept them as true. They're not like
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chronically online. And even if they are, they're not chronically tapped into, you know, the British
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medical journal, family of journals. And so the reality is when a study like this gets published
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and it goes viral and it gets shared and people talk about it on podcasts and people write articles
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about it. That message gets out to people and the retraction message statistically just doesn't.
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It doesn't get out to people. And therefore, the impact of saying, oh, well, don't worry about it.
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If we mess up, we'll just retract it. That's not good enough. It simply does not actually do what
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we needed to do, which is go out and reach the people who were misled by this work, whether intentional
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or unintentional, doesn't really matter. We need to convey the message to people that, hey, this
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is not actually a representation of what we know scientifically on the topic. And that is a huge
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issue that is really hard to rectify. It's really difficult to address, what are we going to
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ultimately do about that? How do we have a paper like this that is like super viral and reaches
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all these people? What is the mechanism we have to actually reach out and correct the record and
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give people a better understanding of what actually is true and what actually they should be doing
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in terms of their health, their fitness, their nutrition, whatever. And right now, I think the
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reason that it's important to highlight the timeline and the procedure is like, ultimately,
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at the end of the day, this just doesn't work very well as a system. It takes way too long. It should
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not take the better part of two years to rectify something that, as we talked about in our timeline,
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it took a matter of days to say, hey, this stuff doesn't add up. And so if you want to actually
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try to get corrected information out there, even though you noticed it in a couple days,
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put together your very robust airtight justification, which ends up being more than vindicated on
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a statistical review. You need to, under the current system, settle in for what is essentially going
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to be about two years. It's going to take about 100 emails. It's going to be sometimes tense,
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back and forth. Sometimes researchers won't answer you at all, which is actually a reasonably
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pleasant way it could go. Sometimes they get very defensive and there have been notable situations
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in the past, not in this paper, where people start getting litigious, threatening to sue you for
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poking around, or a variety of unpleasant things you have to deal with. Sometimes the journals will
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act like they're going to charge you two or three grand to have the privilege of helping them correct
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the record. So it's just overall a really, really bad system. And I don't bring this up just to
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complain, although it may be warranted in this case. But I bring this up because it brings me to a
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few conclusions that I think are worth addressing to the iron culture audience who, by and large,
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I think views itself as being science-based or evidence-based. First and foremost, a conclusion
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to walk home to take away or to take home from this whole saga is, turns out, apple cider vinegar
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does not work better than ozempic. It does not increase energy expenditure more than DNP.
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Who knew? Who knew? But it turns out that that's not the case. Another conclusion that I think should
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be an absolute, an absolute travesty and a scandal is that this whole saga that I just explained
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is actually an example of the system working. So I'm sure James won't mind me sharing this,
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but James has tapped into that world of people who kind of do this and kind of shine a light on
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research that they believe may be potentially unreliable and then investigations follow up and
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sometimes there's retractions and things of that nature. And believe it or not, as tedious and
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protracted and annoying is that whole process sounded, this is actually a smooth and fairly
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expeditious run through the process. In many cases, this process will take way longer.
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The people who are just trying to get the scientific record corrected often end up getting in
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situations where people threaten to sue them or actually sue them. And so as crazy as it sounds,
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this process, if you had no context for it, you would look at it and say, well, that was a mess and
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took way too long and was way too hard on the people who were just trying to flag research that
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was clearly unreliable and proved to be unreliable. But at the end of the day, that went well,
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relative to the norm, which is a problem for not just for researchers, but for people who use
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research because who knows how many papers in the next 600 days are going to get retracted that
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are currently being believed and put into practice, put into application. Another conclusion that's
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really important to highlight is this is going to get a lot worse, I think. I am not making any
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claim about why there's a massive degree of disagreement between the data spreadsheet and the
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tables in the paper that we've talked about up to this point. I don't know how that came to be,
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and therefore I won't comment on how that came to be. But I will say this, getting away from that
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paper and getting into the broader context, okay, I want to be very clear about that.
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It has never been easier with AI tools to just generate a fake data set that doesn't look
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quite as silly as what people may have done in the past. If a person wanted to fabricate a data set,
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they could do that using AI tools in a way that is not at this point, I don't think it would be
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full proof, but it would be a lot more convincing than in the past. Now people who actually know how to
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use numbers and stuff could actually, even without AI tools, they could be up to far more
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malicious things in a much more convincing way, but even people who aren't that good with numbers,
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I think if they've felt inclined to fabricate a data set or embellish a data set, I think that's
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easier than it's ever been. And on top of that, it's easier than it's ever been to very quickly
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generate a paper using large language models. And then you get reviews in from the peer reviewers,
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and it's never been easier or quicker to quickly generate a response to those reviewers using
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large language models. So what I'm getting at is clearly we've never been good as a world of
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publishing scientists at actually doing this or trying to stay on top of doing it in a prompt
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or expeditious way, but in a system that is likely to get flooded with a much higher number of
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total submissions and by extension unreliable submissions in the years that follow, I expect that
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this is going to get a lot worse and a lot harder to, a lot harder to, to ultimately correct
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or police. So yeah, I'm very concerned about just the sheer volume of kind of flooding a system
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that already seems to be working at a rate and with a success rate that seems to indicate that
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it's already not doing so well. I think flooding it with more papers more quickly is just going to
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stress and severely challenge an already very challenged system. So now getting into stuff that's
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actually practical here, what do we do with this? Why does this matter? When we say that we're going
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to be evidence-based or science-based as it pertains to our training, our exercise, our nutrition,
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our health, whatever, when you say I'm evidence-based or I'm science-based, at the end of the day,
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that is really a declaration of your perspective. That's a statement of epistemology, meaning I am
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declaring what kind of evidence I find to be valuable, what kind of evidence I find to be useful,
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I'm implying a certain hierarchy of different types of evidence and how I wish to apply them.
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I am signaling and declaring that I think the scientific method is a good idea. I think that
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objective scientific research is generally a good way to learn as much as we can about the world
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around us and what we observe in this world. So that's pretty much what you're saying. It is not
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saying once something hits PubMed, I'm locked in, whether I like it or not, whether I agree with it
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or not, whether I think it's reliable or valid or not, once it hits PubMed, it is officially
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science and I am bound to it. That is not what being evidence-based is and frankly, that is a very
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poor approach to trying to be evidence-based or science-based. In reality, a person who is
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evidence-based realizes that once a paper hits PubMed, once a paper hits that journal's website,
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that is where the actual evaluation and implementation of evidence begins, not where it ends.
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I know this has been said a million times, so I won't belabor the point. But being evidence-based
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or being science-based does not mean I am forever required to have a PubMed link to justify
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everything I do. Someone who's evidence-based, as it pertains to nutrition or training, is someone who
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says, I have my own experiences and those are valuable. I have an understanding of broad
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recommendations and guidelines that are widely accepted by authorities in the space
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that is also a source of information. Aside from those, also the experiences of people who have
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accomplished a lot in the endeavors that I'm interested in, that is also valuable information
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and in addition, peer-reviewed, well-controlled, scientific studies are a very, very good source of
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information as well. An evidence-based practice is combining all of those things.
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But what's really important is that for every type of information you wish to combine
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into your evidence-based practice or your science-based practice, there needs to be a level of
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evaluation that happens before it's all entered into this big mixing bowl of information we're
spk_0
going to act upon. So what that means is, with your own observations and anecdotes, you should be
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constantly challenging yourself on those. A good example is when I was in college, I remember my
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freshman year, I started taking an herbal dietary supplement that was marketed for muscle growth.
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I really believed in it because the marketing was good and I was a more trusting person at that
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stage in my life and a much more optimistic person as well. So I started taking this herbal supplement
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and I grew like a weed. I got very big, very strong, very quickly and I had convinced myself,
spk_0
very strongly, man, this supplement is incredible. I can't believe the gains that it is giving me.
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In hindsight, and I've recognized this shortly after this kind of honeymoon period believing
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that this supplement was just incredible, I looked back at it and I said, you know what, I'm a
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never had this level. I lived like a hundred yards from my gym if that. It was open all the time.
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There was even a gym in the dorm basement that was, I mean, I don't think the university knew it existed.
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So it was unofficially open 24 hours a day and you can just go in there and it was actually
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like reasonably well equipped. So all that is to say, I had never enjoyed this unfettered level of
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access to really solid training opportunities. I never had this much free time because I probably
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should have been going to more classes than I was. And I also was on a meal plan. So I was steps
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away from a dining facility, which was all you can eat. And honestly, if you followed my content
spk_0
in any capacity, you know that I am not a food snob. So I was in heaven, like all the food as far
spk_0
as I could tell was incredible. So in hindsight, I looked back and I said, was it really the supplement?
spk_0
Or is it possible that you just really like lifting all day, sometimes multiple times a day,
spk_0
and eating unlimited amounts of reasonably high quality food? Could also that have had something
spk_0
to do with these gains you were making? So all that is to say, when you're leaning on your own
spk_0
experiences and your anecdotes, you still have to really challenge and interrogate those before you
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kind of put those in the mix in terms of dictating decision making. And we see this all the time as
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well when people are trying out different programs and they convince themselves, you know, this program
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works for me. This one doesn't therefore, I guess I only respond to low volume stuff or I only
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respond to high volume stuff. You start digging deeper. And in many cases, you'll challenge
spk_0
the initial assumptions that you make as you're kind of making these preliminary observations.
spk_0
Same thing goes when we're incorporating anecdotes from other people. If our personal anecdotes
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sometimes end up being unreliable, then certainly we have to question anecdotes from people for whom
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they're talking about observations, experiences that we didn't even see with our own eyes, right? So
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of course, we need to take those anecdotes and observations with a grain of salt because we couldn't
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possibly, we could not possibly have the whole story when someone is kind of walking us through it.
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We don't know if they say, oh, I did this program. I had the best gains ever. We don't really know
spk_0
what their diet was like day to day, their stress levels, you know, was it just this incredible
spk_0
opportunity like I was talking about to have low stress, low work obligations, just train in all day,
spk_0
eating all day. Who knows if they were using other things to supplement their gains. So other
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people's anecdotes, we have to obviously scrutinize very carefully. Expert consensus is usually
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measured, but it oftentimes represents a pretty good snapshot of where the evidence is at a
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given point in time. But those types of consensus statements and papers are certainly not infallible.
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Sometimes they will be led by people who have a lot of sway on the final report or the final
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publication. And they may have some kind of pet theories that get treated with an inappropriate
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lack of scrutiny. And so you will see some unreliable things sneak in from time to time. And then,
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of course, those things tend to expire at the end of the day. You know, sometimes years pass,
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we learn more about the topic and ultimately things that were believed to be true are either
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severely updated or in some cases even overturned depending on where the research leads. So
spk_0
all these sources of information require a great deal of scrutiny and skepticism. And at the end
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of the day, published peer-reviewed scientific research is no different. Now, obviously,
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I live a life of science. I'm in the lab every morning dealing with my urine samples,
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getting the machine going for the day for our doubly labeled water analysis. I publish frequently
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in scientific journals. So I don't want to give the impression that I have become some kind of
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cynical, nihilistic person who believes that there's no point to all this. If that were the case,
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I would probably be having a severe identity crisis and or I wouldn't say a midlife crisis,
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but I also wouldn't say a quarter life crisis. So a third life crisis maybe. I'd be going through it
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if that was really where I was at mentally. That's not where I'm at mentally.
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However, I do have a high level of concern that a lot of stuff is getting published that
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shouldn't. And when the process of rectifying that takes 600 days and maybe a couple thousand
spk_0
dollars and maybe 100 emails and you're treated like a nuisance the whole time you're doing it,
spk_0
which dissuades you from doing it in the future. It's a very thankless thing. It's a very
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inefficient process. I'm very concerned that if we continue as scientists to pretend that
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that system is adequate, we're going to continue to publish first and ask questions later.
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We're going to continue to publish unreliable information. That unreliable information is going
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to reach way more people than the eventual retraction notice. And ultimately we will be contributing
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as scientists to a system where people will start to correctly take note of the fact that
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I guess now with published science, I'll say now even though it's always been true, but
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you have to take it with a big grain of salt. Now that's always going to be true, but I think
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now more than ever as a scientific community, we have to be really cautious about how hard we're
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working to earn and preserve the trust of the non-scientific community. I have concerns about
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that and then when it comes specifically to the fitness space, I just think it's really critical that
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we have to be very, very skeptical of research that gets published. We have to scrutinize it very
spk_0
carefully. It's okay to really dig into the research, reach out to multiple content creators in
spk_0
the space that you trust and say, hey, this seems weird to me. What do you think? This seems odd to
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me. What do you think? These two papers seem like they are fully contradictory. What do I make of this?
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At the end of the day, I think that that dialogue is going to be really critical. If we want to have
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like a metaphorically healthy, robust science-based or evidence-based lifting community that's using
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research to inform our training and our nutrition, unfortunately we cannot rely on the journals themselves
spk_0
to play defense against some of these unreliable papers and prevent them from getting published. We
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need to have what is often called secondary or post-publication peer review happening within the
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lifting community. We have to have chatter and discussion and debate and sometimes that debate
spk_0
may get animated, may get tense depending on people have their pet theories. This paper supports
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that paper rejects it. People get into some heated debates over this stuff and of course we should
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be able to do it in a very measured, reasonable way. But that more than ever, I think that debate,
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disagreement, conversation, that is really critical for making sure that the evidence is ultimately
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bolstering what we're trying to do with our training and nutrition rather than hindering it or
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getting in the way. We looked to research for increased clarity more so than we looked to it for
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confusion. Sometimes confusion is an intermediate step we have to take. Sometimes research findings
spk_0
at first don't make sense. Then we replicate them and replicate them and replicate them and we
spk_0
realize, oh, we had it all wrong from the start. We shouldn't be quick to outright refute everything
spk_0
that initially doesn't really make a ton of sense. But we have to remember to keep those good
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practices in mind, which is one paper or a couple papers with some indicators that they could be
spk_0
unreliable, could be shady. Those things come out. We don't need to immediately rush to application.
spk_0
Sometimes we do have to remember to slow our horses a little bit to kind of take a slow measured
spk_0
approach and say, let's wait to see if this actually gets replicated. Let's try to make sense
spk_0
of this in the context about other literature and sometimes being the slow one to move ultimately
spk_0
pays off because you don't end up chasing these random things that proved to be unreliable.
spk_0
So just within the last couple of years, I've kind of written pretty extensively about these two
spk_0
papers that have been ultimately retracted. One of them was on ice baths. The other was on apple cider
spk_0
vinegar. Now, what is the probability of absolute tragedy if you took those papers at face value?
spk_0
At the end of the day, it pretty low probability, right? There have been rare but very severe
spk_0
adverse effects associated with some people doing ice baths that really shouldn't have been.
spk_0
They were not in the cardiovascular condition to do it or they were doing it dangerously out in
spk_0
water that was too deep. You'll see rare instances where people will have cardiac events or
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accidental drownings from certain approaches to cold water like ice baths or cold water immersion.
spk_0
But by and large, usually the downside of doing cold water immersion is that you wasted 15 minutes
spk_0
of extreme discomfort for no tangible output, which is annoying but again, not a tragedy.
spk_0
With apple cider vinegar, maybe you had to take a shot for a while of something that you didn't
spk_0
really enjoy. If you're taking it as a shot non-dioluted, maybe you did a modest level of negative,
spk_0
a modest level of harm to your tooth enamel because of how extremely acidic it is.
spk_0
But again, we're not talking about outright tragedies here. But I think the real downside of
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especially with these kind of hot topic papers that keep getting published and then retracted is
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at a certain point, we're going to lose as a scientific community the trust of people.
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And at a certain point, it's like, well, if we keep doing this, do we deserve it in the first place?
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And the answer is probably no. So that's why not to turn this into some kind of advertisement,
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but that's why we, the folks of the Mass Research Review, and many research reviews like us,
spk_0
we find it so important to, and it's the reason we do this podcasting, it's the reason we do research
spk_0
reviews is unfortunately relying on the journals to do their own business and do their work effectively.
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It's not the best approach these days unless you're willing to be wrong for a couple of years and
spk_0
then say, oh, okay, never mind. So I want to extend this as a challenge to the science-based or
spk_0
evidence-based lifting community talk. You already do, but keep it up. Talk early, talk often,
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talk regularly with zeal when it comes to new research that comes out. It is important that we
spk_0
kind of work as a whole community to stress test these new findings that catch our attention.
spk_0
Approach them with open-mindedness, but also with skepticism and scrutiny. Have those conversations
spk_0
about what we think we can or cannot take away from this research and ultimately, you know,
spk_0
put out a variety of perspectives about where the research currently stands, which paper seem
spk_0
to be reliable and which ones seem not to be. That's not to make it some kind of huge witch hunt
spk_0
where every paper is presumed to be guilty until proven innocent with this extreme level of skepticism,
spk_0
but we got to keep our eyes open and we got to, whatever new paper comes out, if it absolutely
spk_0
stuns us, those are important conversations to have because, you know, one of the things I'm
spk_0
really happy about, one of the things I'm not going to lie, I'm really proud about it is
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with that ice bath paper and with this paper, people near me were not taking it seriously,
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and they save themselves the trouble and the confusion about a year or two before there was
spk_0
any kind of indication coming back from the journals. What frustrates me is that even with our
spk_0
best efforts, we know that, like I said with the ice bath paper, that reached 6 million people,
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and I'm not reaching 6 million people to remind them, hey, actually that wasn't legit. With the
spk_0
Apple cider vinegar paper, again, we can look at those alt metric scores and say, okay, we saw what
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193 news outlets share the original paper. Are we going to have a 193 that share the
spk_0
retraction notice? Of course not. We'd be lucky to get to 30, I think. I'd love to be wrong about
spk_0
that, but I've seen a handful and these kinds of, you know, a retraction notice does not have a
spk_0
long tail in terms of the news picking it up. Basically, you get a little flash in the pan,
spk_0
and it's probably going to dry up pretty soon here. So if I had to guess, by the time it's all said
spk_0
and done, the ratio of news outlets to cover it versus the original paper versus news outlets to
spk_0
cover the retraction notice, it'll probably end up being like 193 to 25-ish. And usually the news
spk_0
outlets that cover the retractions are not, they're not the ones that people actually,
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they're not the ones that have massive readership. You know, you get there like really big,
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the really big kind of lay press sites that will say, hey, apple cider vinegar to lose 15 pounds
spk_0
in 12 weeks, but then it's like some some blog that's like dedicated to like science, literacy,
spk_0
and statistics that'll eventually cover the retraction. And like what they do is very important
spk_0
work and they do it, you know, a lot of those outlets do it quite well, but their readership is like
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100,000 of what you get in some of the on lay press outlets that will cover the flashy news story
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when it appears to work, but they never really quite get around to putting out a new article saying,
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by the way, never mind, forget all that. So briefly, I'm going to check in on the chat here.
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Like I said earlier, my mistake, my personal apology to the Iron Cult, I will bring back the jazz
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music. It will be, I don't know if it will be for next episode, but it will be coming, bear with me,
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folks. See, chimed in. First of all, the comment, flaky helms. I don't know any other way to put it.
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This is a flaky man. He cannot be relied upon, but we do wish him well in whatever he's up to as he
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skips yet another episode of Iron Culture. Another comment here from C says, I just lost 20 pounds
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the hard way if only it were this easy. So yeah, I mean, it would be great if again, instead of spending 500,
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thousand dollars on ozemic and, you know, running the risk of the low probability, but, you know,
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substantive adverse effects that could occur. Yeah, the shot of Apple cider vinegar sounds pretty good
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compared to that, but unfortunately, it doesn't work out. A question was, where did Apple cider vinegar
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get such a cult following to begin with? That I honestly do not know. All I know is it's been bouncing
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around the kind of fitness wellness world for quite some time. I do believe that it varies
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regionally. There are some regions of the world where it has a lot more cultural purchase than
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others, but in any case, it is big. And I want something kind of gets that that reputation for being
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this kind of like wellness-oriented remedy for lack of a better term. It really takes a long time
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for that to go away. So I think Apple cider vinegar is going to be around for a while. I wouldn't
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bother using it for any outcome, really, but I don't expect it to go quietly into the night just
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because this one paper was retracted. Got a comment about AI paper mills. Yeah, paper mills have always
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been a thing. These are basically entities, you know, small collections of people who kind of just
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churn out these academic papers that are very low quality, sometimes nonsensical, but they just kind
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of churn them out and get them submitted to journals and just try to push them through the publication
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process. You might be wondering why, but there's all sorts of weird incentive processes or incentive
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structures that would lead one to pursue that process. But back in the day, if you were going to do
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a paper mill, someone had to actually sit down and write the thing. Even though it was rubbish, mostly,
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they still had to do it. But like I was saying with my concerns, you know, it seems that
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it's never been easier to run a paper mill. That's for sure. And frankly, you probably don't even
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need as much of a paper mill these days if your whole goal is to just get something out the door
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with AI tools. It's never been easier. And I do fear the short-term impact that will have on journals.
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Now, and not just journals, but the scientific literature is really what I care about.
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Having said that, some optimism, theoretically, these journal publishing companies who are worth
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very large amounts of money should be able to find creative ways to leverage AI tools for the good
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of the journals' rigor and processes. So I certainly wouldn't discount that, but I definitely think
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it's a game of cat and mouse. And I think the mouse is winning right now relative to the cat.
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And I hope that the cat in this metaphor, the publishing companies, the journal publishers,
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I hope that they will catch up in a meaningful way. And I do believe that there is promise for
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those tools to be developed, but they're probably already developed. They need to be implemented at
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scale in a way that's actually useful and effective. Another comment here, a question I should say,
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how are the incentives about doing replications versus novel research structured in academia?
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It's getting better, but there's much more fanfare and prestige and therefore incentive
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to publish totally novel original research more so than trying to replicate something that has been
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found previously. I think that compared to all other times in human history, it's never been
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more appreciated to do replication research, but we still certainly have not gotten to the point
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where that is viewed as an equal contribution to the literature by any means. And that's ultimately
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a problem. If we are of the belief that the value of science is adding knowledge, improving the
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knowledge base of the published literature, in theory, we would incentivize this kind of work
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of identifying papers that that were at retraction. In theory, removing an unreliable paper from the
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literature, I think should be just as valuable as adding a new reliable paper to the literature.
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Replicating a finding should be viewed as just as valuable as an original finding. At the end of the
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day, they're all going to be little data points on a meta analysis. And frankly, when you look at that
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forest plot or that funnel plot, once the meta analysis is done in 20 years, you're never really
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going to look at it and say, yeah, but who came out first? And so I think we are broadly adopting that
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that perspective of really embracing meta science and looking at the big picture rather than
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the whole idea that it was so much more valuable to publish something novel. I think that ultimately
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comes down to like this old school view of the career of a scientist or academic more so than what is
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good for learning and the literature itself. So for example, you could really make a name for yourself
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by identifying the trexular theory of blank with this novel finding, the first to do it.
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And of course, it's valuable to have people seeking to be innovative and to learn new things
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about the world. But the idea that being the first to the punch is necessarily advantageous or good
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or valuable. That is from my view exclusively a career slash ego oriented perspective. I want to be
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the first because then it's my discovery. Whereas if the main concern really was just making sure
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that we had robust scientific literature to lean on, the first to find it is no more valuable than
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the third to find it. And frankly, not until we have the second third and fourth to find it, do we
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actually, what we actually want to really hang our hat on that set of observations. So I think that we
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are broadly slowly moving away from that model of everyone trying to be the first to something.
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I think we're understanding the value more as a collective scientific community of I think we're
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more appreciating the value of replication. And so we still have a lot of work to do in terms of
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rectifying some of those incentive structures, but they're definitely to be optimistic. They're
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definitely moving in the right direction for sure. So great comments and questions in the chat over
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there in the iron culture chat. I want to make sure that I'm answering both chats. So let me pop in
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here. Yeah, I think I got to everything that I could see. So hopefully people in both chats feel
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adequately listened to that they've gotten adequate attention during this live recording of the
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iron culture podcast. I'm just going to zoom out real quick. Yeah. So everyone, I want to thank you
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once again, as my light turns off for joining in on a live recording of iron culture. I really appreciate
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all the comments, all the questions, all the support as always. Once again, if you like the show and
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you want to do what you can to support many ways to do it, make sure that you like, rate, subscribe,
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review, make sure you go over to massresearchreview.com and consider becoming a member of the mass community.
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Definitely make sure that you're supporting our dear, dear friends over at Elite FTS. Fantastic
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folks over there. Like I said, I've been using their products for well over a decade. And finally,
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as I was killing time and saying the things that are burned into my memory, I navigated over to
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the other live chat. So I just want to make a quick, I want to quickly address some of the comments
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over there. I did the mass live chat now. I'm in the iron culture live chat. So Dylan said, Helms
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is going to be here to show his commitment to the cult, right? And the answer is no. As we've
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already seen regrettably, I don't know what his commitments are to, but it's definitely not the cult.
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Got a lovely good night message from Eduardo. Good night. Sleep well. Appreciate you popping into
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the chat. Steven says it's Dr. Trexler versus Big Vinegar. Absolutely it is. It is frightening to go
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up against a massive industry like this. We know that they have unlimited power, unlimited wealth.
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They could make a person like me go away very easily, but I'm willing to take on the vinegar lobby
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and the vinegar mafia, so to speak. So we'll see how it goes. But if anything negative were to
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happen to me, certainly the vinegar barons are the culprits for sure. And then Dylan said,
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it's really sad. My nutrition professor is an RD and once stated in our class, taking apple cider
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vinegar is one of the health, healthiest things you can do. Yikes, Dylan. Yikes. I am going to be
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charitable and pretend that there is some kind of context that I'm not understanding in which that
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would be a defensible thing to say, but my initial reaction is Yikes, Dylan. Yeah, so if you
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were going to talk about what are some of the healthiest things you could do to wrap up the show
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here. Apple cider vinegar, I don't believe it would make my top 1000 healthiest things to do.
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Number one is be physically active. Number one, and number two is eat a balance diet with adequate
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macro and micronutrition. Certainly things on the short list would be avoid smoking.
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If you're going to drink alcohol, do it in moderation, get adequate sleep, develop and maintain
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close social bonds and a good social network in your local community. Identify something that gives
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your day and in more broader terms your life a great sense of purpose such that you feel connected
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to things bigger than yourself. We could go on a very long list before we ever got to
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apple cider vinegar. So that is very troubling. And Dylan has challenged me in the 11th hour
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of the show metaphorically to do my whole top 1000. So I tell you what, Dylan, stay tuned.
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So the next issue of mass is coming out in a couple days, October 1st, November or December 1st.
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Make sure you tune in to see if I've decided to list as an article in mass my top 1000 things to do
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for your health. I'm not committing to it. I'm certainly not guaranteeing it. But if it keeps
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you on the edge of your seat, Dylan, you can think about the possibility of me listing out 1000 healthy
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things. And we can take bets on whether or not apple cider vinegar will show up somewhere in the
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980 to 1000 range time will tell. All right, folks. As always, thanks so much for joining me.
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I really appreciate you checking in. We will be back with another episode in seven days. But
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until then, everyone have a fantastic week and take care of yourself.
Topics Covered
Iron Culture podcast
evidence-based fitness
apple cider vinegar weight loss
nutrition science
retracted research paper
GLP-1 weight loss drugs
BMJ Nutrition Prevention and Health
energy expenditure
DNP metabolism
weight management strategies
critical analysis of research
fitness content creators
mass research review
Elite FTS discount code
science-based nutrition