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Record W3192816370 · doi:10.53102/2014.33.02.773

Mise en place d’un modèle de mesure des performances et d’amélioration du système de management de la logistique

2014· article· fr· W3192816370 on OpenAlexaff
Fettah Elmajdouly, Abdelfetah Adil, Saïd Ouaskit, Mbarek Elbounjimi, Aziz OUAHBANE

Bibliographic record

VenueRevue Française de Gestion Industrielle · 2014
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicQuality and Supply Management
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsHumanitiesPhysicsPhilosophy

Abstract

fetched live from OpenAlex

Cet article présente les résultats des travaux de développement d'un nouveau modèle de mesure des performances et d'amélioration du système de management de la logistique pour les entreprises industrielles. Ce modèle s'inspire des principes du système de management de la qualité ISO 9000 (AFNOR, 2005) principalement l'approche processus, l'approche système et la boucle d'amélioration continue PDCA. La fonction logistique est traitée d'une manière détaillée avec une focalisation sur la planification et la gestion intégrée des flux physiques, informationnels et financiers. Le modèle SMLOG a été validé par application à un cas pratique au sein d'une entreprise industrielle.

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)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.023
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0050.004
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.024
GPT teacher head0.230
Teacher spread0.205 · 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 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

Citations0
Published2014
Admission routes1
Has abstractyes

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