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Record W1532274257

Environmental Adaptations Related to Winter for Travelers with Visual Impairment

2010· article· en· W1532274257 on OpenAlexaboutno aff
Agathe Ratelle, Julie-Anne Couturier, Julie Landry, Carole Zabihaylo

Bibliographic record

VenueTRANSED 2010: 12th International Conference on Mobility and Transport for Elderly and Disabled PersonsHong Kong Society for RehabilitationS K Yee Medical FoundationTransportation Research Board · 2010
Typearticle
Languageen
FieldPsychology
TopicSafety Warnings and Signage
Canadian institutionsnot available
Fundersnot available
KeywordsFacilitatorAdaptation (eye)PedestrianNegotiationGeographyPsychologyVisual impairmentOrientation (vector space)Transport engineeringApplied psychologyEngineeringPolitical scienceSocial psychology
DOInot available

Abstract

fetched live from OpenAlex

Winter constitutes one of the greatest environmental barriers for people with a physical impairment, especially individuals with visual disabilities. During winter, many orientation and mobility tasks of visually impaired (VI) pedestrians are affected, for instances, keeping line of direction on the sidewalk, establishing and maintaining orientation, and negotiating street crossings with safety. A survey with a group of experienced winter blind travelers had initially been conducted to determine the major problems, strategies and best facilitators during winter travel. The worst problem mentioned was walking on ice. Quick and appropriate city maintenance services were reported as the main facilitator. With regards to environmental adaptations, Accessible Pedestrian Signalization (APS) was mentioned as a facilitator for street crossing. The value of this adaptation in winter conditions will be discussed. Efficiency of other environmental adaptations for VI people, such as warning and guidance tiles, is now explored in Montreal (Canada).

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)0.002
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 score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.043
GPT teacher head0.380
Teacher spread0.337 · 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

Citations0
Published2010
Admission routes1
Has abstractyes

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Same venueTRANSED 2010: 12th International Conference on Mobility and Transport for Elderly and Disabled PersonsHong Kong Society for RehabilitationS K Yee Medical FoundationTransportation Research BoardSame topicSafety Warnings and SignageFrench-language works237,207