Bibliographic record
Abstract
Weight problems are defined as a not unusual chronic sickness of excessive frame fat and has grown to be a global epidemic that is no longer the handiest gift within industrialized international but also in many growing and even underdeveloped nations. At gift, the prevalence of weight problems (described as body mass index [BMI] ≥ 30 kg/m2) is within the range of 15 – 30% in the growing populations in Europe, North America, and many Arabic international locations, with an unequivocal trend for in addition, increases [1]. This circumstance will increase the risk of growing diffusion of negative results to human health ranging from metabolic disturbances, type 2 diabetes mellitus (T2DM), and cardiovascular headaches to problems with locomotor machines and many types of cancer [2]. In addition, weight problems impair the subjective nice of life in affected human beings and can reduce existence expectancy [3]. Although there is a very specific relationship between excessive frame weight and the risk of diabetes, obesity may additionally result in many other disturbances that can aggravate the diabetic state.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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".