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Record W189508827

Traffic Signal Warrant Handbook

2007· article· en· W189508827 on OpenAlexaboutno aff
Sharif Hussein Sharif Zein, A A Guebert

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicReliability and Maintenance Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsWarrantSIGNAL (programming language)Matrix (chemical analysis)Component (thermodynamics)Computer scienceOperations researchEngineeringBusiness
DOInot available

Abstract

fetched live from OpenAlex

This handbook provides traffic operations practitioners with a guide to using the Canadian Traffic Signal Warrant Matrix Procedure. The Traffic Signal Warrant Handbook describes the matrix warrant methodology, and is intended to help the practitioner understand the principles and assumptions behind the procedure. The handbook identifies the input data required for the warrant analysis and describes how each of the warrant components is calculated. A number of case studies are presented in the handbook, with variations on each case study, to help the practitioner comprehend the application of the matrix warrant methodology and the sensitivity of each component within the methodology. The handbook will help to ensure that the Canadian Traffic Signal Warrant Matrix Procedure is applied in a consistent and comprehensive way and is supported by software to perform the matrix procedure. (A)

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.936
Threshold uncertainty score0.350

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 communication0.0000.000
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 head0.005
GPT teacher head0.180
Teacher spread0.175 · 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 designSimulation or modeling
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
Published2007
Admission routes1
Has abstractyes

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