Feasibility of an interdisciplinary program for obesity management in Canada.
Bibliographic record
Abstract
OBJECTIVE: To assess the feasibility of a medically supervised, publicly funded interdisciplinary program for obesity management in a Canadian setting. DESIGN: Retrospective chart audit using electronic medical records. SETTING: Wharton Medical Clinic in Hamilton and Burlington, Ont. PARTICIPANTS: A total of 2739 consenting patients attending the interdisciplinary obesity-management program at Wharton Medical Clinic. MAIN OUTCOME MEASURES: Three- and 6-month weight changes and factors affecting weight loss. RESULTS: The 1085 patients attending the clinic for at least 3 months (mean [SD] of 8.1 [6.1] visits and 5.4 [4.7] months) lost a mean (SD) of 4.2 (7.1) kg or 3.5% (6.8%) of their initial body weight, with 32% and 9% of these patients attaining weight reductions of 5% or greater and 10% or greater, respectively. The 289 patients attending the clinic for 6 months or more (mean [SD] of 13.2 [9.7] visits and 10.5 [6.9] months) lost a mean (SD) of 5.4 (10.6) kg or 4.3% (9.2%) of their initial body weight, with 47% and 17% attaining reductions of 5% or greater and 10% or greater, respectively. Visit frequency was positively associated with weight loss independent of age, sex, body mass index, and treatment duration. CONCLUSION: Preliminary data support the short-term effectiveness and clinical utility of this publicly funded program. Using this interdisciplinary model, approximately half of patients were able to attain clinically significant weight loss.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".