Bibliographic record
Abstract
Excess weight represents a critical and common health problem in Canada. The last survey of a national representative sample based on measured anthropometrics has been conducted in 1992. According to surveys using measured data, the prevalence of obesity (body mass index, BMI = 30.0 kg m(-2)) between 1970 and 1992 for those aged 20-69 years increased from 8% to 13% in men and 13% to 15% in women. The proportion of Canadians displaying a BMI > or =25.0 kg m(-2) increased from 47% to 58% in men and from 34% to 41% in women in the same period. The most recent prevalence estimates from self-reported data in a national representative sample indicated that 15% of the adult population (> or =18 years) was affected by obesity, while an additional 33% was classified in the overweight category (BMI 25.0-29.9 kg m(-2)) in 2003. However, it has been suggested that self-reported height and weight underestimate the prevalence of obesity by approximately 10%. Canadian children, aboriginal populations, and immigrants are some of the vulnerable groups particularly at risk of excess weight or for which the increase in the recent decades has been greater than the national increase. The increases in overweight and obesity over the past 30 years among Canadians have been dramatic. It will be possible to precisely analyse the current situation and its evolution in the last 10 years when data based on measured height and weight will be released, that is, in 2005 and after.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".