The Third International Congress on Physical Activity and Public Health: Toronto, May 5−8, 2010
Bibliographic record
Abstract
Katzmarzyk is Guest Editor of this special issue of the Journal of Physical Activity and Health. He is with Pennington Biomedical Research Center, Baton Rouge, LA, and is Chair of the Scientific Program Committee, Third International Congress on Physical Activity and Public Health. deaths annually.8 The scientific program for the Toronto Congress was arranged under 4 main tracks: 1) physical activity and health, 2) surveillance and public policy, 3) physical activity interventions, and 4) community and public health promotion strategies. The scientific program was designed after extensive consultation with experts in the field, and there was an international call for symposia proposals and abstracts. The final program consisted of 6 pre-congress workshops, 5 keynote lectures, 28 symposia, 48 oral free communications, and 525 poster presentations. In addition, a well-attended post-congress workshop saw the launch of the revised Canadian pre-participation screening questionnaires, the PAR-Q and PARmed-X (now called the PAR-Q+ and the Online PARmed-X). This special issue of the Journal of Physical Activity and Health is a legacy of the Third International Congress on Physical Activity and Public Health. Three keynote lectures as well as summaries of all 28 symposia are contained in this volume. Further, the Toronto Charter for Physical Activity, which was presented and ratified in the final keynote session, is reproduced in its entirety in English, French, Spanish, and Portuguese. The Charter is a call to action to improve opportunities for physical activity worldwide and is an advocacy tool to influence decision makers at national, regional, and local levels. We live in exciting times, and the level of excitement in our field is palpable. People around the world are beginning to recognize the benefits of a physically active lifestyle, and our challenge now is to implement sustainable, cost-effective, evidence-based interventions to shift the physical activity level of the entire population upwards in every country.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.173 | 0.069 |
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".