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Record W2105515017 · doi:10.1603/022.038.0515

Responses of the Crucifer Flea Beetle to<i>Brassica</i>Volatiles in an Olfactometer

2009· article· en· W2105515017 on OpenAlexafffund
Margaret Y. Gruber, Ning Xu, Larry Grenkow, Xiang Li, Joseph C. Onyilagha, Juliana J. Soroka, Neil D. Westcott, Dwayne D. Hegedus

Bibliographic record

VenueEnvironmental Entomology · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect Pest Control Strategies
Canadian institutionsAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsOlfactometerBiologyCruciferLinaloolFlea beetleBotanyGeraniolGreen leaf volatilesAllyl isothiocyanateIsothiocyanateBrassicaEssential oilEcology

Abstract

fetched live from OpenAlex

A suite of commercially available volatile compounds was tested in an olfactometer bioassay for responses by the crucifer flea beetle (Phyllotreta cruciferae). Flea beetles were inhibited by exposure to hexane, pentane, and ethanol. Allyl-isothiocyanate, a crucifer-specific volatile, was moderately attractive to spring and early fall flea beetles, but inhibitory to late fall flea beetles. Spring flea beetles were most attracted to (+)-sabinene and E-beta-ocimene, and 1-hexanol, 1-pentanol, and Z-3-hexen-1-ol were stronger attractants than allyl-isothiocyanate. Spring beetles were strongly inhibited by (-)-E-caryophyllene, beta-ionone, indole, (+/-)-linalool, (+)-limonene, E-geraniol, and (-)-beta-pinene and moderately inhibited by (-)-verbenene and hexenal. Our study showed that older leaves and flowers of Brassica napus variety AC Excel contained small amounts of beta-ionone, but seedlings did not. beta-Ionone has not been documented previously in B. napus.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.016
GPT teacher head0.226
Teacher spread0.210 · 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

Citations50
Published2009
Admission routes2
Has abstractyes

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