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Record W4287646081

Étude des performances agronomiques de cultures conduites en agriculture biologique et à destination de l'alimentation humaine dans un contexte de marais

2020· preprint· fr· W4287646081 on OpenAlexaff
Maïté de Sainte Agathe

Bibliographic record

VenueOrganic Eprints (International Centre for Research in Organic Food Systems, and Research Institute of Organic Agriculture) · 2020
Typepreprint
Languagefr
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsCégep de Saint-Laurent
Fundersnot available
KeywordsForestryGeography
DOInot available

Abstract

fetched live from OpenAlex

Ce stage, réalisé au sein de l’unité expérimentale INRAe de Saint-Laurent-De-La-Prée, avait pour principal objectif de mieux identifier les cultures destinées à l’alimentation, ainsi que les motivations et attendus des agriculteurs biologiques face à ces cultures. Pour cela, des entretiens semi-directifs ont été réalisés auprès de 14 agriculteurs biologiques, dans le but de savoir quelles cultures ils produisaient, pourquoi ils avaient choisi de les produire et quel était leur rapport à la production destinée l’alimentation humaine. Les cultures identifiées, en plus des céréales « classiques » étaient la lentille, le lin, le quinoa, le chanvre, l’oeillette, le soja, le millet blanc, le sarrasin, le colza et le pois chiche. Pour chaque culture, on peut constater que les attentes et les motivations varient, selon par exemple si la culture est une légumineuse ou non, le choix se portant sur telle ou telle culture en fonction du système de culture choisi par l’agriculteur.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.076
GPT teacher head0.351
Teacher spread0.275 · 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 designObservational
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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueOrganic Eprints (International Centre for Research in Organic Food Systems, and Research Institute of Organic Agriculture)→Same topicAgriculture and Rural Development Research→French-language works237,207→