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Record W2562384215

Evaluation de la technique d’exclusion par filets pour gérer les ravageurs en pomiculture

2016· article· fr· W2562384215 on OpenAlexaboutno aff
Raphaël Haraz, Dominique Fleury

Bibliographic record

VenueRevue suisse de viticulture, arboriculture et horticulture · 2016
Typearticle
Languagefr
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsnot available
Fundersnot available
KeywordsForestryHorticultureBiologyGeography
DOInot available

Abstract

fetched live from OpenAlex

Les insectes ravageurs sont de plus en plus resistants aux matieres actives appliquees. Les filets d’exclusion constituent une alternative aux insecticides pour lutter contre les ravageurs. Deux systemes de lutte par filets d’exclusion ont ete evalues contre des ravageurs pomicoles a Victoriaville (Quebec, Canada). D’autres parametres tels que le climat sous le filet et l’incidence de la tavelure (Venturia inaequalis) ont ete egalement mesures. Les resultats ont ete positifs contre les deux principaux ravageurs de la pomme presents dans les vergers quebecois: la tordeuse a bandes obliques (Choristoneura rosaceana) et la punaise terne (Lygus lineolaris). Les systemes mono-rang et mono-parcelle ont reduit les degâts de C. rosaceana et L. lineolaris respectivement de 8,2 a 2,8 et 4,4 % et de 14,3 a 7,3 et 5,4 %. Les filets ont malheureusement profite a d’autres ravageurs secondaires dont certains pucerons, un probleme recurrent dans la lutte par exclusion. Les filets d’exclusion semblent prometteurs dans la lutte contre plusieurs ravageurs en pomiculture.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.260
Teacher spread0.253 · 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 designBench or experimental
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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