2013 Abstracts and Posters: Canadian Pharmacists Association Conference, Charlottetown, PEI
Bibliographic record
Abstract
introduction: medical complications of obesity are numerous.pharmacists can have a role in helping patients lose weight to help them manage some of their medical conditions. oBJEctiVE:to provide a weight management service to patients as part of a comprehensive approach to health and wellness. MEtHodS:the weight loss program was developed and then advertised in the pharmacy and at the local hospital.physicians' offices were also notified of the weight loss program through fax.patients who would benefit from weight loss to better manage their chronic illnesses were identified through medication reviews.Upon initial consult, weight, height, waist circumference, fasting blood glucose level and blood pressure were measured.some patients on cholesterol medications provided cholesterol level results from their physician if available.patients were weighed and measured weekly.blood pressure was measured at the onset and the end of the program for all patients and weekly in those individuals whose blood pressure was initially elevated.A medication review follow-up was also incorporated into the process for those individuals on medications for the treatment of hypertension or diabetes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.465 | 0.100 |
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".