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Record W1982167337 · doi:10.1016/j.envint.2011.02.003

Improving health through policies that promote active travel: A review of evidence to support integrated health impact assessment

2011· review· en· W1982167337 on OpenAlexaff
Audrey de Nazelle, Mark Nieuwenhuijsen, Josep M. Antó, Michael Bräuer, David Briggs, Charlotte Braun‐Fahrländer, Nick Cavill, Ashley R Cooper, Hélène Desqueyroux, Scott Fruin, Gerard Hoek, Luc Int Panis, Nicole Janssen, Michael Jerrett, Michael Joffe, Zorana Jovanovic Andersen, Elise van Kempen, Simon Kingham, Nadine Kubesch, Kevin M. Leyden, Julian Marshall, Jaume Matamala, Giorgos Mellios, Michelle A. Méndez, Hala Nassif, David Ogilvie, Rosana Peiró, Katherine Pérez, Ari Rabl, Martina S. Ragettli, Daniel A. Rodrı́guez, David Rojas, James F. Sallis, J. Terwoert, Jean‐François Toussaint, Jouni T. Tuomisto, Moniek Zuurbier, Erik Lebret

Bibliographic record

VenueEnvironment International · 2011
Typereview
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsUniversity of British Columbia
FundersEconomic and Social Research CouncilCoca-Cola Foundation
KeywordsHealth impact assessmentEnvironmental planningHealth benefitsBusinessEnvironmental healthPublic healthMedicineEnvironmental scienceNursing

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.010
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.015
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.024
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0070.005
Bibliometrics0.0080.011
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.255
GPT teacher head0.493
Teacher spread0.238 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations615
Published2011
Admission routes1
Has abstractno

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