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 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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".