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Record W2177462512 · doi:10.1603/0046-225x-32.4.742

Comparative Behavioural Responses of<i>Dryocoetes confusus</i>Swaine,<i>Dendroctonus rufipennis</i>(Kirby), and<i>Dendroctonus ponderosae</i>Hopkins (Coleoptera: Scolytidae) to Angiosperm Tree Bark Volatiles

2003· article· en· W2177462512 on OpenAlexaff
Dezene P.W. Huber, John H. Borden

Bibliographic record

VenueEnvironmental Entomology · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsDendroctonusBark beetleBiologyBark (sound)Green leaf volatilesMountain pine beetleBotanySemiochemicalBuprestidaeNonanalPheromoneCurculionidaeEcologyFood scienceHerbivore

Abstract

fetched live from OpenAlex

Synthetic, angiosperm bark-derived volatiles, which elicit antennal responses in a number of coniferophagous bark beetles (Coleoptera: Scolytidae), were tested in groups for their ability to disrupt the pheromone-positive response of the spruce beetle (SB), Dendroctonus rufipennis (Kirby), the western balsam bark beetle (WBBB), Dryocoetes confusus Swaine, and the mountain pine beetle (MPB), Dendroctonus ponderosae Hopkins, to attractant-baited traps. One complex mixture disrupted WBBB response to pheromone-baited multiple-funnel traps to a level not significantly different than that in unbaited control traps. No group of compounds, including a group of green leaf volatiles, was active in disrupting SB response, a result that contrasts other published findings and that is different from the behavioral responses that are elicited by nonhost volatiles in other species of coniferophagous bark beetles. For the MPB, the two green leaf alcohols, 1-hexanol and (Z)-3-hexen-1-ol, were highly disruptive. In addition, combinations of compounds from the group consisting of salicylaldehyde, benzaldehyde, nonanal, guaiacol, benzyl alcohol, and conophthorin acted to augment the disruptive activity of the green leaf alcohols.

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)0.000
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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.015
GPT teacher head0.238
Teacher spread0.223 · 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 teacher head, not a consensus.

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

Citations15
Published2003
Admission routes1
Has abstractyes

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