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Record W2594090028 · doi:10.1061/jtepbs.0000047

Improved Pedestrian Sight-Distance Needs at Railroad-Highway Grade Crossings

2017· article· en· W2594090028 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Transportation Engineering Part A Systems · 2017
Typearticle
Languageen
FieldEngineering
TopicTransportation Safety and Impact Analysis
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPedestrianIntersection (aeronautics)SightPedestrian crossingGeometric designTransport engineeringTangentLevel crossingComputer scienceSimulationEngineeringMathematicsGeometryPhysics

Abstract

fetched live from OpenAlex

This paper presents an improved model for pedestrian crossing time that is used to establish preliminary guidelines for lateral clearance needs on railroad-highway grade crossings. The improved model includes new elements that are lacking in existing models such as pedestrian observation-reaction time, length of pedestrian unit, and safety margin. A general model for the required lateral clearance, that is applicable to any number of tracks on crossings located on horizontal curves or on tangent sections, was developed. The model can be used to determine the required lateral clearance to the right and to the left of the crossing, including maximum lateral clearance, its location, and lateral clearance at a specified location. A comparison of pedestrian crossing sight distance with intersection (vehicle) sight distance shows that lateral clearance needs for pedestrians are not generally satisfied by those currently available for vehicles. The presented design guidelines promote pedestrian safety and should be of interest to highway and railroad professionals.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.728
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.015
GPT teacher head0.227
Teacher spread0.212 · 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