Bibliographic record
Abstract
Nicole E De Long, Alison C Holloway Department of Obstetrics and Gynecology, McMaster University, Hamilton, ON, Canada Abstract: The global prevalence of obesity has been increasing at a staggering pace, with few indications of any decline, and is now one of the major public health challenges worldwide. While obesity and metabolic syndrome (MetS) have historically thought to be largely driven by increased caloric intake and lack of exercise, this is insufficient to account for the observed changes in disease trends. There is now increasing evidence to suggest that exposure to synthetic chemicals in our environment may also play a key role in the etiology and pathophysiology of metabolic diseases. Importantly, exposures occurring in early life (in utero and early childhood) may have a more profound effect on life-long risk of obesity and MetS. This narrative review explores the evidence linking early-life exposure to a suite of chemicals that are common contaminants associated with food production (pesticides; imidacloprid, chlorpyrifos, and glyphosate) and processing (acrylamide), in addition to chemicals ubiquitously found in our household goods (brominated flame retardants) and drinking water (heavy metals) and changes in key pathways important for the development of MetS and obesity. Keywords: obesity, pesticides, polybrominated diphenyl ethers, heavy metals, acrylamide, endocrine-disrupting chemicals
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".