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Record W6955608791 · doi:10.58079/12s3k

Données géospatiales issues du recensement agricole européen

2024· article· fr· W6955608791 on OpenAlexaboutno aff

Bibliographic record

VenueIndustrias Culturais (Universidade de Coimbra) · 2024
Typearticle
Languagefr
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsnot available
Fundersnot available
KeywordsEconomic shortageContext (archaeology)LimitingQuarter (Canadian coin)

Abstract

fetched live from OpenAlex

Les données géospatiales issues du recensement agricole (Eurostat) fournissent des informations relatives à la situation géographique d’une exploitation, et des informations plus détaillées sur la structure des exploitations.La grille qui contient les données géoréférencées est d’une taille minimale de 1 km de côté, imbriquées dans des grilles de plus en plus grandes (5 km, 10 km, 20 km, 40 km ou 80 km, par exemple). La taille des cellules de la grille varie en fonction du respect des aspect...

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)0.017
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.152
Threshold uncertainty score0.302

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0100.023
Science and technology studies0.0010.000
Scholarly communication0.0050.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0220.007

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 head0.043
GPT teacher head0.254
Teacher spread0.211 · 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
GenreDataset

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
Published2024
Admission routes1
Has abstractyes

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Same venueIndustrias Culturais (Universidade de Coimbra)→Same topicAgriculture and Rural Development Research→French-language works237,207→