Mitch Naughton's Avatar

Mitch Naughton

@mitchnaughtonphd.bsky.social

PhD in Exercise Science | Lecturer in Exercise Physiology | Understanding Load, Fatigue, Recovery, and Systems Thinking

708 Followers  |  378 Following  |  28 Posts  |  Joined: 27.08.2023  |  2.1047

Latest posts by mitchnaughtonphd.bsky.social on Bluesky


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πŸ†• The effects of isothermic heat acclimation on simple and complex cognitive performance in the heat
www.tandfonline.com/doi/full/10....

03.02.2026 14:45 β€” πŸ‘ 1    πŸ” 1    πŸ’¬ 0    πŸ“Œ 0
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Jerzy Neyman: A Positive Role Model in the History of Frequentist Statistics Many of the facts in this blog post come from the biography β€˜Neyman’ by Constance Reid . I highly recommend reading this book if you find ...

Always worth going back to this @lakens.bsky.social piece on an influential statistician who *wasn’t* personally a piece of shit. daniellakens.blogspot.com/2021/09/jerz...

31.01.2026 22:04 β€” πŸ‘ 20    πŸ” 4    πŸ’¬ 0    πŸ“Œ 0
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Alison Luchs, who has worked at the National Gallery of Art for 47 years, agreed to learn Gen Z slang and make videos because she wanted to raise interest in the museum’s art.

She never expected to slay. https://wapo.st/45BXc3S

29.01.2026 13:01 β€” πŸ‘ 2580    πŸ” 699    πŸ’¬ 38    πŸ“Œ 199
Screenshot of tweet from Huberman that reads: β€œThe other is that dog breeds w/different shaped heads are predictive of their demeanor and intelligence. And while I don’t! believe in Phrenology I now do pay some attention to how the shapes of peoples heads relates to their intellect and steadiness, or lack thereof.”

Screenshot of tweet from Huberman that reads: β€œThe other is that dog breeds w/different shaped heads are predictive of their demeanor and intelligence. And while I don’t! believe in Phrenology I now do pay some attention to how the shapes of peoples heads relates to their intellect and steadiness, or lack thereof.”

In response to announcement that he will be a new CBS contributor, Andrew Huberman tweeted β€œI’ve always gone issue-by-issue on health & science, spoken to experts w/a range of takes & presented where I see the center of (data) mass pointed. I’ll do the same with @CBSNews”. In Sept he posted this:

28.01.2026 01:44 β€” πŸ‘ 7349    πŸ” 1862    πŸ’¬ 518    πŸ“Œ 676
Figure shows carbohydrate intake equivalent (grams per hour) as a function of power output (watts) from 100-400 W, for a range of isolines of RER (respiratory exchange ratio) from 0.7 to 1.00 (equivalent to the range of metabolic intensity). Each RER also has a band for gross metabolic efficiency (GE), which results in greater uncertainty for energetic output and therefore caloric and g/hr carb intake requirement.
Figure titles: What is the plausible range of carbohydrate intake required to match 100% glycogen expenditure per hour?
THIS IS NOT A RECOMMENDATION
RER will be lowest at rest, somewhere in the middle in β€œzone 2”, and highest at and above FTP functional threshold power. Uncertainty ranges for GE derived from Ettema & LorΓ₯s, 2009. Efficiency in Cycling. A Review. https://www.researchgate.net/publication/24027428_Efficiency_in_cycling_A_review.

Figure shows carbohydrate intake equivalent (grams per hour) as a function of power output (watts) from 100-400 W, for a range of isolines of RER (respiratory exchange ratio) from 0.7 to 1.00 (equivalent to the range of metabolic intensity). Each RER also has a band for gross metabolic efficiency (GE), which results in greater uncertainty for energetic output and therefore caloric and g/hr carb intake requirement. Figure titles: What is the plausible range of carbohydrate intake required to match 100% glycogen expenditure per hour? THIS IS NOT A RECOMMENDATION RER will be lowest at rest, somewhere in the middle in β€œzone 2”, and highest at and above FTP functional threshold power. Uncertainty ranges for GE derived from Ettema & LorΓ₯s, 2009. Efficiency in Cycling. A Review. https://www.researchgate.net/publication/24027428_Efficiency_in_cycling_A_review.

Carb intakes are increasing among endurance athletes

But there is wide uncertainty in how much we actually expend, depending on absolute power output, relative intensity, and gross metabolic efficiency

Which factor has the biggest influence depends where we are on the map #rstats #datavis #cycling

08.01.2026 22:51 β€” πŸ‘ 8    πŸ” 1    πŸ’¬ 1    πŸ“Œ 0
Figure showing metabolic energy expenditure (kcal) as a function of power output (W) and external work output (kJ) from 100-400 W (400-1400 kJ), for a range of isolines of GE (gross metabolic efficiency).
Figure titles: What is the plausible range of internal metabolic energy expenditure (kcal) for a given external work output (kJ), as a function of power output (W) over 60-minutes.
GE is proportional to power output and intrinsic mechanical and metabolic factors, typically around 20%. The effect of intensity (RER; respiratory exchange ratio) on energy expenditure is minimal when compared to influence of external work output and GE. A 1:1 ratio of external work to internal energy expenditure is only accurate at the highest GE of ~25%.

Figure showing metabolic energy expenditure (kcal) as a function of power output (W) and external work output (kJ) from 100-400 W (400-1400 kJ), for a range of isolines of GE (gross metabolic efficiency). Figure titles: What is the plausible range of internal metabolic energy expenditure (kcal) for a given external work output (kJ), as a function of power output (W) over 60-minutes. GE is proportional to power output and intrinsic mechanical and metabolic factors, typically around 20%. The effect of intensity (RER; respiratory exchange ratio) on energy expenditure is minimal when compared to influence of external work output and GE. A 1:1 ratio of external work to internal energy expenditure is only accurate at the highest GE of ~25%.

Typical range for GE = 15-25%

Assuming 25% is not the best estimate

GE = 25% (ie. 1kJ power output on bike computer == 1 kcal energy intake) will probably UNDERestimate energy expenditure and intake requirements for most athletes, at most realistic power outputs #rstats #datavis #cycling

08.01.2026 22:51 β€” πŸ‘ 4    πŸ” 1    πŸ’¬ 4    πŸ“Œ 0

A PhD is a driving test. A postdoc is practice. You know that your students and postdocs will eventually be able to drive in directions you can’t or won’t. And it’s wonderfull. But it’s important not to mistake an unexciting work product with the actual value.

30.11.2025 06:42 β€” πŸ‘ 13    πŸ” 1    πŸ’¬ 2    πŸ“Œ 0
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Autism, Microbiomes, & Mice Burying Marbles with Kevin Mitchell

Grateful to the Decoding the Gurus guys for having me on to discuss Autism, Microbiomes, & Mice Burying Marbles... @guruspod.bsky.social cc @statsepi.bsky.social @deevybee.bsky.social 😊 open.spotify.com/episode/01w8...

19.11.2025 09:32 β€” πŸ‘ 41    πŸ” 10    πŸ’¬ 2    πŸ“Œ 1
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Recent #Research by Fabio G. Laginestra et al. examines the influence of biological sex on the #metabolic basis of skeletal muscle #fatigue in vivo πŸ”¬ 🧲

πŸ“œ Read the study here: physoc.onlinelibrary.wiley.com/doi/10.1113/...

19.11.2025 12:02 β€” πŸ‘ 2    πŸ” 1    πŸ’¬ 0    πŸ“Œ 0
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CSIRO to cut up to 350 research jobs in major overhaul After 440 positions were slashed last year, the CSIRO has announced more staff cuts across the country in a bid to remain financially viable.

Where to start, with a statement like this?

"Tim Ayres said the cuts were aimed at refocusing … CSIRO towards research priorities, such as critical minerals, iron & steel production in Australia."

From some rando down the bus stop, one would brush it off.

But this is from our Science Minister 🀯

19.11.2025 00:10 β€” πŸ‘ 95    πŸ” 48    πŸ’¬ 5    πŸ“Œ 8

When I'm right, I'm right; and when I'm wrong, I'm just trying to create a teachable moment.

17.11.2025 15:13 β€” πŸ‘ 36    πŸ” 6    πŸ’¬ 1    πŸ“Œ 0
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Finally, someone has solved a real problem with AI! No more having to take a paper in the format for a journal that rejected you, and reformat it for a new journal. Well done!! formatmypaper.com

15.10.2025 06:33 β€” πŸ‘ 464    πŸ” 146    πŸ’¬ 17    πŸ“Œ 39
AI Slop Is Destroying The Internet
YouTube video by Kurzgesagt – In a Nutshell AI Slop Is Destroying The Internet

The real Butlerian Jihad is not againt AGI, but against AI slop? Happy weekend to all www.youtube.com/watch?v=_zfN...

11.10.2025 07:08 β€” πŸ‘ 32    πŸ” 5    πŸ’¬ 4    πŸ“Œ 1
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a man drinking from a can that says science on it ALT: a man drinking from a can that says science on it

Okay I’m officially done on X/Twitter. In dire need of a healthy science community with people posting interesting takes on research. Where are my nutrition and metabolism people…? 🍎

03.10.2025 18:52 β€” πŸ‘ 4    πŸ” 1    πŸ’¬ 1    πŸ“Œ 0

bsky.app/profile/adam...

30.09.2025 08:49 β€” πŸ‘ 2    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0

None of which is helpful I realise! All the best with whatever you decide to do.

25.09.2025 20:32 β€” πŸ‘ 1    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0

I don’t regret it at all, but it was a very stressful time and I certainly didn’t cope very well at the time. Pandemic definitely contributed to that. Worked out in the end.

25.09.2025 05:56 β€” πŸ‘ 3    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0

I had this issue during my PhD - one supervisor left during COVID and another wasn’t prepared to take me on. I spent about 6 months trying to find my own exit as the uni did not help me. Once I secured the exit I moved uni’s and I never looked back, but I also lost my scholarship for a time.

25.09.2025 05:55 β€” πŸ‘ 4    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0

Too late, Batman. Once this Tylenol floods the city's water supply, my wiki won't run out of editors ever again

22.09.2025 21:54 β€” πŸ‘ 19090    πŸ” 5522    πŸ’¬ 49    πŸ“Œ 54

Idles?

21.09.2025 23:59 β€” πŸ‘ 0    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0

Finished marking papers in one of my courses. It's painful to see bright minds atrophied by the integration of LLMs into the "learning" process.

Instead of building an understanding, e.g. by trying to generalize examples seen in exercises, LLMs are used in an effort to "just do". Poorly.

Shame.

18.09.2025 14:38 β€” πŸ‘ 11    πŸ” 1    πŸ’¬ 1    πŸ“Œ 1
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The influence of biological sex on the metabolic basis of skeletal muscle fatigue in vivo Abstract figure legend Women are often reported to develop less muscle fatigue than men during physical activity. By combining electrical femoral nerve stimulation and phosphorus magnetic resonance s...

The influence of biological sex on the metabolic basis of skeletal muscle fatigue in vivo
physoc.onlinelibrary.wiley.com/doi/10.1113/...

18.09.2025 17:43 β€” πŸ‘ 20    πŸ” 3    πŸ’¬ 0    πŸ“Œ 0
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You can see exactly where Wightman’s tank emptied, about 5-10 m from the line (by the Honda sign). If you calculate his critical speed and D’ from his outdoor PBs, D’ was gone 6 m before the line.

18.09.2025 06:51 β€” πŸ‘ 5    πŸ” 2    πŸ’¬ 0    πŸ“Œ 0
Converlens - Engagement, insights and analytics platform for surveys and consultations Collect, Manage and Analyse surveys, consultation data and text

What do you think about Australia "associating with" Horizon Europe?

It's not me asking, but the Department of Industry, Science and Resources.

If you're interested, make a submission to their "request for information": ▢️ consult.industry.gov.au/association-...

12.09.2025 04:17 β€” πŸ‘ 11    πŸ” 7    πŸ’¬ 1    πŸ“Œ 0
Abstract: Under the banner of progress, products have been uncritically adopted or
even imposed on users β€” in past centuries with tobacco and combustion engines, and in
the 21st with social media. For these collective blunders, we now regret our involvement or
apathy as scientists, and society struggles to put the genie back in the bottle. Currently, we
are similarly entangled with artificial intelligence (AI) technology. For example, software updates are rolled out seamlessly and non-consensually, Microsoft Office is bundled with chatbots, and we, our students, and our employers have had no say, as it is not
considered a valid position to reject AI technologies in our teaching and research. This
is why in June 2025, we co-authored an Open Letter calling on our employers to reverse
and rethink their stance on uncritically adopting AI technologies. In this position piece,
we expound on why universities must take their role seriously toa) counter the technology
industry’s marketing, hype, and harm; and to b) safeguard higher education, critical
thinking, expertise, academic freedom, and scientific integrity. We include pointers to
relevant work to further inform our colleagues.

Abstract: Under the banner of progress, products have been uncritically adopted or even imposed on users β€” in past centuries with tobacco and combustion engines, and in the 21st with social media. For these collective blunders, we now regret our involvement or apathy as scientists, and society struggles to put the genie back in the bottle. Currently, we are similarly entangled with artificial intelligence (AI) technology. For example, software updates are rolled out seamlessly and non-consensually, Microsoft Office is bundled with chatbots, and we, our students, and our employers have had no say, as it is not considered a valid position to reject AI technologies in our teaching and research. This is why in June 2025, we co-authored an Open Letter calling on our employers to reverse and rethink their stance on uncritically adopting AI technologies. In this position piece, we expound on why universities must take their role seriously toa) counter the technology industry’s marketing, hype, and harm; and to b) safeguard higher education, critical thinking, expertise, academic freedom, and scientific integrity. We include pointers to relevant work to further inform our colleagues.

Figure 1. A cartoon set theoretic view on various terms (see Table 1) used when discussing the superset AI
(black outline, hatched background): LLMs are in orange; ANNs are in magenta; generative models are
in blue; and finally, chatbots are in green. Where these intersect, the colours reflect that, e.g. generative adversarial network (GAN) and Boltzmann machine (BM) models are in the purple subset because they are
both generative and ANNs. In the case of proprietary closed source models, e.g. OpenAI’s ChatGPT and
Apple’s Siri, we cannot verify their implementation and so academics can only make educated guesses (cf.
Dingemanse 2025). Undefined terms used above: BERT (Devlin et al. 2019); AlexNet (Krizhevsky et al.
2017); A.L.I.C.E. (Wallace 2009); ELIZA (Weizenbaum 1966); Jabberwacky (Twist 2003); linear discriminant analysis (LDA); quadratic discriminant analysis (QDA).

Figure 1. A cartoon set theoretic view on various terms (see Table 1) used when discussing the superset AI (black outline, hatched background): LLMs are in orange; ANNs are in magenta; generative models are in blue; and finally, chatbots are in green. Where these intersect, the colours reflect that, e.g. generative adversarial network (GAN) and Boltzmann machine (BM) models are in the purple subset because they are both generative and ANNs. In the case of proprietary closed source models, e.g. OpenAI’s ChatGPT and Apple’s Siri, we cannot verify their implementation and so academics can only make educated guesses (cf. Dingemanse 2025). Undefined terms used above: BERT (Devlin et al. 2019); AlexNet (Krizhevsky et al. 2017); A.L.I.C.E. (Wallace 2009); ELIZA (Weizenbaum 1966); Jabberwacky (Twist 2003); linear discriminant analysis (LDA); quadratic discriminant analysis (QDA).

Table 1. Below some of the typical terminological disarray is untangled. Importantly, none of these terms
are orthogonal nor do they exclusively pick out the types of products we may wish to critique or proscribe.

Table 1. Below some of the typical terminological disarray is untangled. Importantly, none of these terms are orthogonal nor do they exclusively pick out the types of products we may wish to critique or proscribe.

Protecting the Ecosystem of Human Knowledge: Five Principles

Protecting the Ecosystem of Human Knowledge: Five Principles

Finally! 🀩 Our position piece: Against the Uncritical Adoption of 'AI' Technologies in Academia:
doi.org/10.5281/zeno...

We unpick the tech industry’s marketing, hype, & harm; and we argue for safeguarding higher education, critical
thinking, expertise, academic freedom, & scientific integrity.
1/n

06.09.2025 08:13 β€” πŸ‘ 3718    πŸ” 1871    πŸ’¬ 109    πŸ“Œ 381

Our data stewards have started recommending that we no longer use US-based infrastructure for #openscience practices, given the risk of (near-future) censorship, from pre-print and data hosting to preregistration and more. That includes OSF.

03.09.2025 08:22 β€” πŸ‘ 66    πŸ” 46    πŸ’¬ 7    πŸ“Œ 4

Results so stunningly clear they inspired this classic xkcd (xkcd.com/2400/):

01.09.2025 19:32 β€” πŸ‘ 3990    πŸ” 1347    πŸ’¬ 17    πŸ“Œ 21

I don't get how people don't realize that a technology that replaces junior and entry level positions in a field destroys that field.

There's no skipping steps. You have to be a junior before you can be a senior, and if you don't have senior people, you don't have a field.

01.09.2025 04:03 β€” πŸ‘ 5159    πŸ” 2086    πŸ’¬ 63    πŸ“Œ 71

It was a rewarding labour of love to work on this paper with a fantastic team of authors, β€œUnderstanding Treatment Response Heterogeneity Using Crossover Randomized Controlled Trials: A Primer for Exercise and Nutrition Scientists”. @hk-ijsnem.bsky.social journals.humankinetics.com/view/journal...

28.08.2025 17:50 β€” πŸ‘ 12    πŸ” 6    πŸ’¬ 2    πŸ“Œ 0

@mitchnaughtonphd is following 20 prominent accounts