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Record W642382296

Une géographie des transports ferroviaires, routiers et aériens : Chapitre 15. In : Mediterra – Logistique et commerce agroalimentaires, un défi pour la méditerranée

2014· preprint· fr· W642382296 on OpenAlexaff
Marco Spinedi, Eléonora Morganti

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2014
Typepreprint
Languagefr
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsMinistère des Transports
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Dans un contexte de mondialisation et d’une Méditerranée en plein bouleversement sociopolitique, le développement du commerce agricole méditerranéen est de plus en plus déterminé par les capacités des pays à se doter d’infrastructures modernes pour fluidifier les échanges, faciliter la circulation des marchandises et garantir une meilleure sécurité alimentaire. Le chapitre présente les systèmes de transport ferroviaires, routiers, et aériens pour les produits alimentaires dans la Méditerranée.

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)0.000
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.059
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.006
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.002

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 head0.020
GPT teacher head0.245
Teacher spread0.225 · 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
Published2014
Admission routes1
Has abstractyes

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