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Record W2028849835 · doi:10.1097/bot.0000000000000101

Effect of Static Electronic Advertising Signs on Road Safety

2014· article· en· W2028849835 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Orthopaedic Trauma · 2014
Typearticle
Languageen
FieldPsychology
TopicSafety Warnings and Signage
Canadian institutionsTransport CanadaCIMA+ (Canada)
Fundersnot available
KeywordsSign (mathematics)MedicineConfidence intervalControl (management)DaylightAdvertisingTransport engineeringArtificial intelligenceComputer scienceEngineering

Abstract

fetched live from OpenAlex

As technology continues to advance, the outdoor advertising industry is taking advantage of electronic signs, some of which are static electronic signs (SES), with the ability to automatically change the message shown on the sign at regular intervals. Studies indicate that SES has a negative impact on the drivers' visual attention and on vehicle control. However, the actual effects of the SES on the number of collisions have been difficult to prove conclusively. The objective of this article is to generate a clear understanding of the safety impacts of SES on the number collisions by conducting a before-and-after analysis with comparison groups. The analysis was based on a total of 10 SES along the Highway 27 and the Gardiner Expressway of the city of Toronto. The results of the before-and-after study revealed that there was not enough evidence to suggest that these signs have any impact on road safety along the adjacent roadway sections at a 95% confidence interval. The same results were obtained by comparing collisions that occurred during daylight and artificial light.

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)0.003
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.973
Threshold uncertainty score0.797

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.288
Teacher spread0.280 · 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