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Record W299593412

TURNING BOX-COX INCLUDING QUADRATIC FORMS IN REGRESSION. IN: STRUCTURAL ROAD ACCIDENT MODELS. THE INTERNATIONAL DRAG FAMILY

2000· article· en· W299593412 on OpenAlexaboutno aff
Marc Gaudry, Ulrich Blum, Tran Liem

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTraffic Prediction and Management Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsAccident (philosophy)Quadratic equationRegression analysisRoad accidentRoad transportDragStatisticsMathematicsEconometricsTransport engineeringEngineering
DOInot available

Abstract

fetched live from OpenAlex

This paper is the final version of, and cancels, a manuscript widely circulated in Canada, Germany, Sweden, and the United States, usually called: FIQ: Fractional and Integer Quadratic Forms Estimated with the LEVEL algorithm in TRIO, and was prompted by the increasing search for flexible turning functions, for instance in the explanation of how some transport costs might vary with distance, or of how fatal road accident frequency and severity fall might rise and then fall with increased traffic, or of how the impact of alcohol on fatal road accident frequency might be explained in a statistical manner.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.026
metaresearch head score (Gemma)0.064
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.026
Threshold uncertainty score0.136

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.064
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.003
Science and technology studies0.0010.002
Scholarly communication0.0020.005
Open science0.0040.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0180.004

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 head0.017
GPT teacher head0.251
Teacher spread0.234 · 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 source (direct Gemma or distilled Codex), 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
Published2000
Admission routes1
Has abstractyes

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