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Record W6949614937 · doi:10.5281/zenodo.15478357

PESKY PESTS: Climate Change and Pest Interactions in Ontario Vineyards

2025· article· en· W6949614937 on OpenAlexaffabout

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPhytoplasmas and Hemiptera pathogens
Canadian institutionsMcMaster University
Fundersnot available
KeywordsClimate changePEST analysisIntegrated pest managementVineyardAgricultureRange (aeronautics)Effects of global warming

Abstract

fetched live from OpenAlex

When examining the effects of climate change on viticulture, changes to grape physiology, and cultivar adaptation should be considered, along with the implications of grapevine pest interactions. We assess the spotted lanternfly and potato leafhopper in Canada, exploring their distribution, development, and environmental and economic implications. While the potato leafhopper feeds on over 200 agricultural host plants, the spotted lanternfly is a potential future invader, spreading rapidly across the United States of America (1). Predictive niche models and experimental studies on high temperature tolerance suggest further range expansion on a global scale, potentially including Ontario. Spotted lanternfly introduction to the United States of America will be used as a reference point to extrapolate potential outcomes of establishment in Ontario. Pest management strategies and preventative measures will further be explored while emphasising the importance of reducing invasion phenomena. Climate change is an enduring concern, and effective vineyard protection from infestation requires both prevention and mitigation measures. Pests are ecologically destructive and economically costly; thus, governments must continue to research this issue to prevent further pest proliferation and downstream harm.

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)0.000
metaresearch head score (Gemma)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.131

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.059
GPT teacher head0.247
Teacher spread0.188 · 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
Published2025
Admission routes2
Has abstractyes

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