As noted in the 2006 Canadian Clinical Practice Guide-lines on the Management and Prevention of Obesityin Adults and Children, included as a supplement to
Bibliographic record
Abstract
this issue of CMAJ (the full document is available online at www.cmaj.ca/cgi/content/full/176/8/S1/DC1),1 approximately 1 in 10 Canadian children and 1 in 4 adults are already obese (defined as weight greater than the 95th percentile for chil-dren and body mass index [BMI] greater than 30 kg/m2 for adults). However, with an additional quarter of children and more than half of adults classified as overweight, rates of obe-sity are projected to soar. The guidelines include both a review of the current litera-ture as well as highlighted areas for further research in each of the chapters. Caregivers will also find practical summaries of recommendations to guide care. Unlike most other obesity guidelines, this initiative was produced by a multidisciplinary group of health professionals that included physicians, psy-chologists, registered dietitians and bariatric surgeons who attempted to address all aspects of the prevention and man-agement of obesity in children and adults. As a consequence, the guidelines address diet, exercise, the environment, phar-macotherapy, behavioural therapy and surgery. The scope of the work and the effort from the many contributors have re-sulted in a commendable document. The evidence-based approach used to develop the guide-lines is described in chapter 1 of the full document. As part of the methods for data acquisition and literature review, 4 data-
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 | 0.008 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.031 | 0.013 |
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".