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Record W4402053658 · doi:10.1079/9781800623279.0032

<i>Orchestes fagi</i>(L.), Beech Leaf-Mining Weevil / Charançon du hêtre (Coleoptera: Curculionidae)

2024· book-chapter· fr· W4402053658 on OpenAlexaboutno aff
Rob Johns, Natalia Kirichenko, Sara Edwards, Sarah Grauby, Cory Hughes, Koichi Beltrando, Benoit Morin, Emily Owens, Jon Sweeney, Kate Van Rooyen, Marc Kenis

Bibliographic record

VenueCABI eBooks · 2024
Typebook-chapter
Languagefr
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsnot available
Fundersnot available
KeywordsCurculionidaeWeevilBeechBoll weevilBotanyHorticultureBiology

Abstract

fetched live from OpenAlex

The first record of beech leaf-mining weevil, Orchestes fagi , was made in 2011 in Nova Scotia, Canada, and its geographic distribution has expanded in Nova Scotia and into neighbouring provinces. Outbreaks of O. fagi have been devastating to American beech, Fagus grandifolia , in Nova Scotia. Studies of the biology of O. fagi suggest that successful management will require tactics that keep adult densities low or directly target adult weevils. Insecticide options currently available do not appear to impact adult populations. Foreign exploration for parasitoids to import into Canada for biological control was conducted in 2018 and 2019, and 17 parasitoid species associated with O. fagi were identified, including a parasitoid of adult O. fagi . Studies are now needed to study the biology, host range, and potential efficacy of these parasitoids.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.968
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.025

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 head0.210
Teacher spread0.194 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2024
Admission routes1
Has abstractyes

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