Bibliographic record
Abstract
The prevalence of overweight among children in Canada hasincreased dramatically from 15 % in 1977/78 to 26 % in 2004.1This increase portends future increases in incidence of dia-betes, cardiovascular diseases, and other chronic diseases.2,3 Docu-menting trends post 2004 and understanding the underlying factors are fundamental to public health. Canadian studies have shown that rurally residing children and youth are more likely to be overweight than urban residents.4-6 In North America, studies have revealed a higher overweight prevalence in rural populations: diet,7 physical activity8 and low socio-economic status9 have been identified as potential reasons. Limited access to parks and recreational facilities in socio-economically disadvantaged areas hinders children from being physically active and puts them at increased risk of becoming overweight.7,10,11 In addition, residents in neighbourhoods with poor access to healthy foods have more fat in their diet and are more likely to become overweight.7,12 The purpose of this present study is to investigate the urban-rural differences in childhood overweight and its underlying causes in
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.131 | 0.050 |
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".