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Record W2773327033

Maîtriser les adventices dans de nouveaux contextes de production. Leviers techniques & retours d’expériences pour une gestion durable

2016· preprint· fr· W2773327033 on OpenAlexaff
Frédérique Angevin, Laurent Basilico, Céline Denieul, Sabrina Gaba, Antoine Messéan, Étienne Pilorgé, Stéphanie Potok, Alain Basail Rodríguez, Fanny Vuillemin

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2016
Typepreprint
Languagefr
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsImpact
Fundersnot available
KeywordsHumanitiesPolitical scienceArt
DOInot available

Abstract

fetched live from OpenAlex

EA Pôle GESTAD Synthèse des rencontres sur la gestion durable des adventices en grande culture organisées par le GIS GC HP2E et le RMT Florad le 15 décembre 2015 au FIAP à Paris. Cette synthèse est disponible sur le site du GIS, ainsi que sur le site du RMT. EAPôle GESTADSynthèse des rencontres sur la gestion durable des adventices en grande culture organisées par le GIS GC HP2E et le RMT Florad le 15 décembre 2015 au FIAP à Paris. Cette synthèse est disponible sur le site du GIS, ainsi que sur le site du RMT.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.016
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.008
Scholarly communication0.0080.005
Open science0.0010.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0160.002

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 head0.015
GPT teacher head0.239
Teacher spread0.224 · 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
Published2016
Admission routes1
Has abstractyes

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