Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To review the literature about cycling and health, and to provide an overview and discussion of the available evidence. SOURCES OF INFORMATION: were searched in PubMed. Clinical trials, practice reviews, and systematic reviews were included. All reference lists were reviewed for additional articles. MAIN MESSAGE: Climate change is a threat to health. In Canada alone, transportation is the second largest source of greenhouse gas emissions. Active transportation, which is any form of human-powered transportation, can mitigate the health effects of the climate crisis while simultaneously improving the health of people. Physical activity improves overall well-being, as well as physical and mental health. Active transportation, particularly cycling, is a convenient way to meet physical activity targets, reduce risk of disease and all-cause mortality, and derive mental health and social benefits. Family physician advocacy for active transportation has been shown to increase cycling levels in patients compared with no physician advocacy. CONCLUSION: Family physicians can help to increase the level of active transportation at the individual patient level through patient education and behaviour change counseling; at the community level through community education and political advocacy; and at the policy level through partnerships with larger organizations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it