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Record W4289000321

Le véhicule autonome va-t-il transformer en profondeur le transport de marchandises ?

2019· preprint· fr· W4289000321 on OpenAlexaff
El Mehdi Aboulkacem, François Combes

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2019
Typepreprint
Languagefr
FieldEngineering
TopicUrban and Freight Transport Logistics
Canadian institutionsMinistère des Transports
Fundersnot available
KeywordsHumanitiesPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Le transport routier de marchandises est une activité dont une grande partie de l'économie dépend. L'apparition possible à moyen terme de véhicules partiellement ou totalement autonomes est susceptible de modifier profondément les équilibres économiques actuels, tant du côté de l'offre (les transporteurs) que de celui de la demande (les chargeurs). Les transporteurs réorganiseront leur production ; les chargeurs réorganiseront leurs chaînes logistiques. Les coûts pourraient diminuer de façon très importante, mais hétérogène en fonction des secteurs. Pour mieux apprécier les effets éventuels de cette révolution technologique, ce projet de recherche propose d'en modéliser les impacts par une approche fondée sur la théorie d'inventaire. Cette approche permet de modéliser la façon dont les chaînes logistiques vont réagir à une modification de l'offre de transport, avec une prise en compte des coûts directs (ici le transport.) et des coûts indirects (ici, les coûts d'inventaire).

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.144

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0040.005
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0170.002

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 head0.013
GPT teacher head0.193
Teacher spread0.180 · 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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