6.D. Pitch presentations: Ottawa and beyond: health promotion
Bibliographic record
Abstract
ProblemNon communicable diseases (NCD) are leading cause of morbidity and premature death in Croatia.Main risk factors are irregular eating habits, inappropriate physical activity and high blood pressure.35% of females and 48% males in adult population have excessive body weight, and 15% of females and 31% of males are obese.Only 17,1% males and 4,3% females are physically active. Description of the problemCroatian Ministry of Health and Croatian Institute of Public Health have initiated National Program of health promotion "Living Healthy''.Croatian government has adopted this Program as a model of comprehensive intervention with the aim of decreasing behavioral, biomedical and sociomedical risks for NCDs.Program consists of 5 components: health education, physical activity, health and nutrition, health and working place and health and environment, with the goal of comprehensive prevention and inclusion of all age groups in all settings.Program is implemented through 21 county public health institutes in collaboration with local authority and civil society. ResultsHealth education, as component of National Program has become a part of school curriculum; in 120 primary schools in Croatia that do not have sport gyms are introduced polygons for training through Program; paths for walking are established in 8 counties, 4 companies get the title ''Heathy Company'' for promoting health in the workplace, criteria for the food labeling with the pledge 'Living healthy' for the food with higher nutritional have been established, guidelines for
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.016 | 0.011 |
| Insufficient payload (model declined to judge) | 0.169 | 0.030 |
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".