More People, More Active, More Often for Heart Health – Taking Action on Physical Activity
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
Physical inactivity is a leading contributor to increased cardiovascular morbidity and mortality. Almost 500 million new cases of preventable noncommunicable diseases (NCDs) will occur globally between 2020 and 2030 due to physical inactivity, costing just over US$300 billion, or around US$ 27 billion annually (WHO 2022). Active adults can achieve a reduction of up to 35% in risk of death from cardiovascular disease. Physical activity also helps in moderating cardiovascular disease risk factors such as high blood pressure, unhealthy weight and type 2 diabetes. For people with cardiovascular disease, hypertension, type 2 diabetes and many cancers, physical activity is an established and evidence-based part of treatment and management. For children and young people, physical activity affords important health benefits. Physical activity can also achieve important cross-sector goals. Increased walking and cycling can reduce journeys by vehicles, air pollution, and traffic congestion and contribute to increased safety and liveability in cities.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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