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Record W2074743847 · doi:10.3141/2185-09

Evaluation of Roadway Guide Signs at Pearson International Airport in Toronto, Canada

2010· article· en· W2074743847 on OpenAlexaboutno aff
Thomas Smahel, Alison Smiley

Bibliographic record

VenueTransportation Research Record Journal of the Transportation Research Board · 2010
Typearticle
Languageen
FieldPsychology
TopicSafety Warnings and Signage
Canadian institutionsnot available
Fundersnot available
KeywordsTransport engineeringListing (finance)International airportRentingPictogramPoint (geometry)Computer scienceEngineeringBusinessGeographyCivil engineeringMathematics

Abstract

fetched live from OpenAlex

A new terminal building resulting in the expansion of the road network was built at Pearson International Airport in Toronto, Canada. A laboratory study was carried out to assess the effectiveness of the proposed guide signs. Participants' decision times and the accuracy of the lane choices selected to reach a provided destination were measured as they responded to a sequence of road signs guiding them into and out of the airport presented on a desktop computer. The key results were as follows: participants showed high response accuracies and fast response times for signs for airport entry, the split between terminals, and the split between arrivals and departures; signs listing the airport terminals for nine airlines on each sign were associated with excessive response times; the split to parking at the arrivals–departures–parking decision point was misunderstood by one-third to one-half of drivers, who assumed that they could continue to the curbside, expecting to find parking there; and the current widely used car rental pictogram was poorly understood, and a new alternative design was preferred by participants.

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)0.017
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.149
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0130.000

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 head0.102
GPT teacher head0.449
Teacher spread0.347 · 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.

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

Citations4
Published2010
Admission routes1
Has abstractyes

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