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Record W1493955115 · doi:10.1109/vnis.1989.98802

An approach to provision of real-time driver information through changeable message signs

2003· article· en· W1493955115 on OpenAlexaffabout
P.H. Masters, Chris Blamey, W B O'Brien, J Kerr

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTraffic Prediction and Management Techniques
Canadian institutionsMinistry of Transportation of Ontario
Fundersnot available
KeywordsComputer scienceSign (mathematics)Point (geometry)GraphicsReading (process)SightUpstream (networking)Control (management)Metropolitan areaTransport engineeringReal-time computingComputer networkEngineeringArtificial intelligenceComputer graphics (images)

Abstract

fetched live from OpenAlex

A computer-based freeway traffic management system for Highway 401 through Metropolitan Toronto is designed to provide greater utilization of available freeway capacity through rapid detection of incidents and the provision to motorists of real-time information on traffic and roadway conditions ahead. Through the strategic location of changeable message signs upstream of potential diversion point, and at fairly regular intervals along the freeway, a reasonable level of coverage has been achieved. The signs are controlled through a central computer system at the control center connected to each sign by a fiber-optics communications system. At an average speed of 60 km/h, motorists will be within sight of a sign at intervals of 3 to 5 min. The information conveyed is limited to the text messages and graphics which can be displayed, and the effectiveness of the information is dependent on the drivers reading the message displays.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.945
Threshold uncertainty score0.275

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.010
GPT teacher head0.213
Teacher spread0.203 · 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 designNot applicable
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

Citations5
Published2003
Admission routes2
Has abstractyes

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