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Record W2177198241 · doi:10.1603/0046-225x-33.2.221

Semiochemical Disruption of the Pine Shoot Beetle, <I>Tomicus piniperda</I> (Coleoptera: Scolytidae)

2004· article· en· W2177198241 on OpenAlexafffundabout
Therese M. Poland, Peter de Groot, Stephen Burke, David Wakarchuk, Robert A. Haack, R. Nott

Bibliographic record

VenueEnvironmental Entomology · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsNatural Resources CanadaRealNetworks (Canada)Canadian Forest Service
FundersCanadian Forest ServiceNatural Resources CanadaU.S. Forest ServiceMinistry of Natural Resources
KeywordsSemiochemicalCurculionidaeBiologyAttractionBotanyHorticulturePEST analysisFrassKairomonePheromoneEcologyPredationLepidoptera genitalia

Abstract

fetched live from OpenAlex

The pine shoot beetle, Tomicus piniperda (Coleoptera: Scolytidae), is an exotic pest of pine in North America. We evaluated blends of semiochemical disruptants, which included nonhost volatiles and verbenone, for their ability to disrupt attraction of T. piniperda to traps baited with the attractant -pinene and to Scots pine, Pinus sylvestris L., trap logs. In Michigan and in Ontario, Canada, a single blend of nonhost volatiles alone [comprised of 1-hexanol, (Z)-3-hexen-1-ol, (E)-2-hexen-1-ol, 3-octanol, and 1-octen-3-ol] or the nonhost volatile blend combined with verbenone significantly reduced attraction of T. piniperda to attractant-baited traps by 68–77%. Similarly, verbenone plus the nonhost volatile blend or a similar blend without 1-octen-3-ol also significantly reduced attack density of T. piniperda on pine trap logs by 56–74% in both Michigan and Ontario. Although relative responses between the different blends were slightly different between Michigan and Ontario, the recommended operational disruptant consisted of 1-hexanol, (Z)-3-hexen-1-ol, (E)-2-hexen-1-ol, 3-octanol, and verbenone.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.868
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.005
GPT teacher head0.202
Teacher spread0.197 · 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 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

Citations14
Published2004
Admission routes3
Has abstractyes

Explore more

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