Out-running ‘bad’ diets: beyond weight loss there is clear evidence of the benefits of physical activity
Bibliographic record
Abstract
You cannot outrun a bad diet has become a rallying phrase for diet-centric approaches to counteracting obesity and poor metabolic health. The phrase is, in our view, often taken to mean that you simply cannot do enough exercise to successfully lose or manage weight over time. Nonetheless, all weight loss paradigms run through energy balance,1 and the concept that you cannot outrun a bad diet is, in our view, inaccurate. Importantly, the simplicity of the phrase does not consider the multitude of other positive effects that physical activity/exercise (ie, running) have on health beyond weight loss. Evidence shows that you can out-exercise/out-work poor nutritional choices, but most people do not since they do not/will not/or cannot, practically, expend sufficient energy to do so. It is incontrovertible that exercise can and does result in weight loss.2 Nonetheless, behavioural and/or metabolic compensatory mechanisms often lessen the predicted weight loss with exercise induced as opposed to diet-induced energy deficits.2 Viewed through the lens of a weight loss approach to …
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.012 | 0.025 |
| Insufficient payload (model declined to judge) | 0.009 | 0.007 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".