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Record W1779926779 · doi:10.1068/a130070p

Trip Generation of Seniors and the Geography of Walking in Montreal

2015· article· en· W1779926779 on OpenAlexaffabout
Md Moniruzzaman, Antonio Páez, Darren M. Scott, Catherine Morency

Bibliographic record

VenueEnvironment and Planning A Economy and Space · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsPolytechnique MontréalMcMaster University
Fundersnot available
KeywordsTravel behaviorProbit modelOrdered probitGeographyTrip generationTransit (satellite)Transport engineeringComponent (thermodynamics)ProbitPublic transportRegional scienceComputer scienceTRIPS architectureEngineering

Abstract

fetched live from OpenAlex

With the graying of populations across the world, the travel behavior of seniors has become a topic of growing interest in planning and research. Most attention in the field of transportation has been devoted to motorized travel. However, the use of various modes of transportation, including nonmotorized travel, remains to be fully investigated. In this paper the multimodal trip generation of seniors in Montreal Island is studied. Personal, mobility tools, neighborhood, and accessibility variables are considered in a trivariate ordered probit model of three modes: car, transit, and walking. Geographical analysis of the walking component of the model helps to identify locations within the region where walking is more or less prevalent among older adults.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.271
Threshold uncertainty score0.546

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.022
GPT teacher head0.232
Teacher spread0.210 · 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

Citations35
Published2015
Admission routes2
Has abstractyes

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