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Record W4402055252 · doi:10.1079/9781800623279.0019

Cutworms (Lepidoptera: Noctuidae) Affecting Crops on the Canadian Prairies

2024· book-chapter· en· W4402055252 on OpenAlexaboutno aff
Kevin D. Floate, John Gavloski, Vincent Hervet, Jeremy D. Hummel, Jennifer Otani, Udari M. Wanigasekara

Bibliographic record

VenueCABI eBooks · 2024
Typebook-chapter
Languageen
FieldAgricultural and Biological Sciences
TopicInsect and Pesticide Research
Canadian institutionsnot available
Fundersnot available
KeywordsCutwormNoctuidaeLepidoptera genitaliaGeographyAgroforestryAgronomyBiologyEcology

Abstract

fetched live from OpenAlex

There is a complex of cutworm species that are pests in western Canada, with important species including Agrotis orthogonia (pale western cutworm), Euxoa auxiliaris (army cutworm), and Euxoa ochrogaster (redbacked cutworm). Cutworm damage is sporadic and patchy, and as a result is difficult to predict. During outbreak years, insecticide applications and/or reseeding are necessary and yield losses can be significant. Recently, field-collected cutworm larvae were reared in the lab to estimate levels of parasitism, which ranged from 2% to 25%, depending on the province and the year of sampling, and to identify the parasitoid complex attacking cutworms. The parasitoid Cotesia vanessae has now been detected in Manitoba and Alberta and has been studied to determine its fundamental host range and to learn more about its biology. The results of laboratory studies using C. vanessae are reviewed, as are future directions for research on cutworm biological control.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.061
Threshold uncertainty score0.122

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.044
GPT teacher head0.237
Teacher spread0.193 · 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 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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