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Record W2335085753 · doi:10.1177/0739456x15616253

Active Transportation by Transit-Dependent and Choice Riders and Potential Displacement of Leisure Physical Activity

2015· article· en· W2335085753 on OpenAlexaff
Ugo Lachapelle, Lawrence D. Frank, James F. Sallis, Brian E. Saelens, Terry L. Conway

Bibliographic record

VenueJournal of Planning Education and Research · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsUniversity of British ColumbiaUniversité du Québec à Montréal
FundersNational Institutes of Health
KeywordsTransit (satellite)Public transportTransport engineeringPhysical activityTravel behaviorRail transitUrban transitBusinessEngineeringMedicinePhysical medicine and rehabilitation

Abstract

fetched live from OpenAlex

Public transit users are expected to have higher levels of active transportation (AT, walking and bicycling) because they often need to walk to and from transit. Surveys in Baltimore and Seattle ( n = 1,622) revealed that transit users performed more AT than nonusers, especially when dependent on transit. Health benefits and impacts of their limited travel options are discussed. Choice transit riders, who use transit and have a car, and dependent transit riders, who are limited to transit use, are compared for differences in AT and leisure physical activity time (LPA). Less LPA is explored as a consequence of the additional AT.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.182
Threshold uncertainty score0.162

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.073
GPT teacher head0.451
Teacher spread0.379 · 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 teacher head, 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

Citations36
Published2015
Admission routes1
Has abstractyes

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