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Record W3013646843 · doi:10.3390/agriculture10040091

Sustainable Arthropod Management in Quebec Vineyards

2020· article· en· W3013646843 on OpenAlexaffabout
Charles Vincent, Jacques Lasnier

Bibliographic record

VenueAgriculture · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsSustainabilityIntegrated pest managementGeographyViticultureGovernment (linguistics)AgroforestryPEST analysisEnvironmental protectionEnvironmental planningEnvironmental resource managementEcologyBusinessBiologyWineEnvironmental science

Abstract

fetched live from OpenAlex

In Quebec (Canada), viticulture is practiced at the fringe of what is known as a cool climate area. Quebec has a very recent history of viticultural entomology as the first artisanal permit for wine making was issued by the Quebec Government in 1985, and the first formal research project about arthropods associated with vineyards was initiated in 1997. The Quebec viticultural industry has consistently developed over ca. 35 years and, given the prospects of global warming, warmer abiotic conditions will allow to cultivate cultivars of better oenological value. Meanwhile, some invasive species that recently arrived in Quebec are causing concerns because they are threatening the sustainability of pest management programs. In this article, we will review of the evolution of entomological research in Quebec vineyards. We will then treat technology transfer activities that allowed to translate research results into protection programs. Finally, we will discuss new and coming entomological problems that are challenging the sustainability of pest management programs in Quebec vineyards.

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 score0.037
Threshold uncertainty score0.266

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.003
GPT teacher head0.181
Teacher spread0.178 · 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

Citations9
Published2020
Admission routes2
Has abstractyes

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