Regular physical activity across the lifespan to build resilience against rising global temperatures
Bibliographic record
Abstract
Population aging, high prevalence of non-communicable diseases, physical inactivity, and rising global temperatures are some of the most pressing issues in public health of the current century. Such trends suggest that individuals increasingly less equipped to tolerate heat will be increasingly exposed to it, which from a public health perspective is alarming. Nonetheless, future impacts of extreme heat events will depend not only on the magnitude of climate change, but on our ability to adapt by becoming less sensitive and vulnerable. Although physical activity's role in mitigating climate change has received attention, its potential contribution to climate change adaptation and resilience remains largely unaddressed. Accordingly, in this viewpoint, we discuss how regular physical activity throughout life could have an important contribution to adapting to rising global temperatures, allowing to be better equipped to cope with heat-related health hazards and increasing individual and community resilience. This viewpoint constitutes a call for more research into the contribution that physical activity can have in adapting to rising global temperatures and, more broadly, to climate change.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".