The Creation and Implementation of an Electronic Exercise Prescription at an Ontario Family Health Team
Bibliographic record
Abstract
Recent evidence shows that 85% of Canadian adults do not meet the recommended physical activity (PA) guidelines set forth by the Canadian Society for Exercise Physiology (Colley et al. 2011). In Kingston, Ontario, Canada 66% of males and 50% of females are overweight or obese, which may be associated with decreased PA levels among the Kingston community as compared to previous years (Vital Signs 2012). There is unequivocal evidence regarding the importance of physical activity in the prevention of a wide variety of diseases and obesity. Regular PA is inversely related to the occurrence of obesity, cardiovascular disease, type 2 diabetes, hypertension, and other common lifestyle related diseases. CSEP’s suggested 150minutes of weekly PA is a guideline to help Canadians achieve the health benefits and disease prevention associated with regular PA (Haskell et al. 2007). At Queen’s University, located in Kingston, senior students in the School of Kinesiology and Health Studies have been given a chance to make an impact on the PA levels of Kingston residents through the Community-Based Physical Activity Promotion course. By connecting students with a community-based group or organization, the year-long course provides an opportunity for students to practically apply the theories, evidence, and skills discussed in course seminars to the promotion of community PA involvement.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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".