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Record W4406572439 · doi:10.1016/j.pmedr.2025.102974

Independent and joint associations of neighbourhood greenness and walkability with transportational and recreational physical activity among youth and adults in Canada

2025· article· en· W4406572439 on OpenAlexafffundabout
Natalie Doan, Sebastian A. Srugo, Stéphanie A. Prince, Rachel C. Colley, Daniel Rainham, Taru Manyanga, Gregory Butler, Richard Larouche, Sarah E. Turner, Justin J. Lang

Bibliographic record

VenuePreventive Medicine Reports · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsUniversity of ManitobaUniversity of LethbridgeUniversity of Northern British ColumbiaDalhousie UniversityUniversity of OttawaPublic Health Agency of CanadaStatistics CanadaUniversity of Waterloo
FundersGovernment of CanadaPublic Health AgencyPublic Health Agency of Canada
KeywordsWalkabilityNeighbourhood (mathematics)RecreationPhysical activityEnvironmental healthGerontologyLevel designGeographyDemographyMedicinePhysical therapyEcologyComputer scienceSociology

Abstract

fetched live from OpenAlex

Objectives: ) physical activity among a nationally representative sample of urban-dwelling youth and adults in Canada. Methods: , while adjusting for individual and neighbourhood characteristics. Results: . Conclusion: Living in a neighbourhood that is both greener and more walkable was more strongly associated with higher transportational, but not recreational, physical activity, than either feature alone. These novel findings highlight the importance of designing cities that are both greener and more walkable to promote active living.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.004
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.011
GPT teacher head0.235
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2025
Admission routes3
Has abstractyes

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