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Record W3048815065

Étude de l’impact de l’implantation d’une voie dynamique réservée aux véhicules à occupation multiple : modélisation analytique et numérique du cas d’étude lyonnais

2019· article· fr· W3048815065 on OpenAlexaboutno aff
Matthias Adam

Bibliographic record

Venuenot available
Typearticle
Languagefr
FieldSocial Sciences
TopicTransportation Planning and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt
DOInot available

Abstract

fetched live from OpenAlex

Les voies de covoiturage sont une des solutions a court terme pour reduire la congestion urbaine dans les grandes metropoles. Elles sont implantees depuis une vingtaine d’annees dans des pays comme les Etats-Unis, le Canada ou encore l’Australie. La Metropole de Lyon, dans le cadre du declassement de l’axe autoroutier A6-A7 qui la traverse du Nord au Sud, reflechit a se doter d’une voie de covoiturage, activee de maniere dynamique aux heures de pointe, pour pallier la forte congestion visible sur l’axe aux heures de pointe. Afin de determiner un perimetre et une duree d’activation coherents, il est necessaire de mener une etude d’impact dans la phase avant-projet. Le LICIT, en synergie avec l’Institut de Recherche technologique SystemX, sont les entites responsables de l’etude. Une representation theorique a l’aide de modeles d’ingenierie du trafic sera effectuee, suivie d’une etude en simulation du cas d’etude. Les resultats seront ensuite compares.

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)0.001
metaresearch head score (Gemma)0.002
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: Empirical
Teacher disagreement score0.145
Threshold uncertainty score0.289

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.019
GPT teacher head0.314
Teacher spread0.295 · 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
Published2019
Admission routes1
Has abstractyes

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Same topicTransportation Planning and OptimizationFrench-language works237,207