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Record W3175499744 · doi:10.4000/books.pup.32150

La coopération, source de performance pour les PSL en Chine

2019· book-chapter· fr· W3175499744 on OpenAlexaff
Tingting Xiang

Bibliographic record

VenuePresses universitaires de Provence eBooks · 2019
Typebook-chapter
Languagefr
FieldHealth Professions
TopicHealthcare Systems and Practices
Canadian institutionsMusée de la Civilisation
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

Au sein des réseaux logistiques, les PSL (Prestataires de Services Logistiques) sont amenés à travailler avec d’autres acteurs afin de gérer les flux de biens et de services le long d’une chaîne de valeur. En quoi coopèrent-ils ? Quels sont les impacts sur la performance logistique ? Dans le cadre d’une recherche doctorale, une enquête menée entre novembre et décembre 2011 sur un échantillon de 134 PSL en Chine nous en donne un aperçu plus clair. Les types de coopération logistique chargeur-...

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)0.005
metaresearch head score (Gemma)0.007
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: Other · Consensus signal: Other
Teacher disagreement score0.032
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.005
Science and technology studies0.0040.009
Scholarly communication0.0130.007
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0220.005

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 head0.042
GPT teacher head0.333
Teacher spread0.291 · 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
GenreOther

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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