Exposure to useable green space and physical activity during active travel: A longitudinal GPS and accelerometer study before and after retirement
Bibliographic record
Abstract
Green spaces may serve as population level interventions encouraging active travel. We examined the associations between exposure to useable green space (CORINE Land Cover categories) and physical activity during active travel (GPS and accelerometer) among late middle-aged participants from the Finnish Retirement and Aging study (n = 102). Greater proportion of useable green space was associated with higher physical activity during active travel on days off (+11 min/day per 1 SD increase in exposure) and on retirement days (+12 min/day), but not on workdays. Thus, it appears that in leisure time, people prefer to engage into active travel in green spaces. • Active travel contributes to physical activity among late middle-aged adults. • Transition to retirement can modify active travel behavior. • GPS and accelerometer data collected before and after retirement were used. • Active travel in green space associated with physical activity on non-working days. • People seem to prefer to engage into active travel in green spaces in leisure time.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".