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Record W560924780

On-road and Laboratory Evaluation of Bilingual Variable Message Signs

2009· article· en· W560924780 on OpenAlexaff
Alison Smiley, Thomas Smahel, D. C. Donderi

Bibliographic record

VenueAdvances in transportation studies · 2009
Typearticle
Languageen
FieldPsychology
TopicSafety Warnings and Signage
Canadian institutionsMcGill University
Fundersnot available
KeywordsSign (mathematics)Significant differenceSign languagePresentation (obstetrics)Computer sciencePsychologyLinguisticsMedicineMathematicsStatisticsSurgery
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this study was to accommodate bilingual (English/French) messages on freeway variable message signs (VMS), while maintaining sign effectiveness. The current English-only 3 line (3L) messages were compared with bilingual 3L messages (using symbols and text) and bilingual 4L messages (text only, 2 lines per language). A calibration study, including on-road and laboratory testing, was used to establish appropriate presentation times for VMS messages in a laboratory study. There was no significant difference in performance between Anglophones and Francophones for the 4L signs or for the English only signs. However, Francophones performed significantly worse than Anglophones on the 3L signs, likely due to lack of separation of the languages. For both Anglophones and Francophones, using colour (to indicate degrees of congestion), on the 3L sign helped improve performance more than adding it on the 4L sign (where it was used to differentiate English (white) and French (yellow), though the effect was a very weak trend. Overall, for both language groups, the 4L sign was preferred.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.819
Threshold uncertainty score0.370

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.039
GPT teacher head0.404
Teacher spread0.365 · 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.

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
Published2009
Admission routes1
Has abstractyes

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