Obesity Management: What Should We Do If Fat Gain Is Necessary to Maintain Body Homeostasis in a Modern World?
Bibliographic record
Abstract
The prevalence of overweight has substantially increased over the last decades despite the intent of health professionals and the general population to prevent this trend. Traditionally, this phenomenon has been attributed to unhealthy dietary macronutrient composition and/or to the decrease in physical activity participation. Beyond the influence of these factors, it is more than likely that other factors have influenced energy balance in a context of modernity. These include inadequate sleep, demanding cognitive effort, chemical pollution, and probably others which also have the potential to promote a positive energy balance but which are also part of the reality of success and productivity in a globalized world. As discussed in this paper, many individuals may become conflicted with themselves if they wish to prevent weight gain while influencing factors which are determinants of their socioeconomic success. In this regard, this paper reminds us of the contribution of adipose tissue gain in body homeostasis which is essential to permit energy balance, especially under lifestyle conditions promoting overfeeding. From a clinical standpoint, this imposes the consideration of a weight loss program as a search for compromise between what can be changed to promote a negative energy balance and what can be tolerated by the body in terms of fat loss. Furthermore, if we also consider the impact of pollution on energy balance for which we currently do not hold solutions of reversibility, we probably must accept that the mankind of today will have to be more corpulent than its ancestors. In this pessimistic environment, there are still possibilities to do better; however, this will probably require the revisiting of lifestyle practices according to what the human body and planet can tolerate as deviation from optimal functioning.
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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 | 0.012 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.015 | 0.017 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".