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Record W2012904316 · doi:10.1603/ec14041

Improving Detection Tools for Emerald Ash Borer (Coleoptera: Buprestidae): Comparison of Multifunnel Traps, Prism Traps, and Lure Types at Varying Population Densities

2014· article· en· W2012904316 on OpenAlexaff
Damon J. Crook, Joseph A. Francese, Michael L. Rietz, D. R. Lance, Helen M. Hull‐Sanders, Victor C. Mastro, Peter J. Silk, Krista Ryall

Bibliographic record

VenueJournal of Economic Entomology · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsOntario Forest Research InstituteNatural Resources Canada
Fundersnot available
KeywordsEmerald ash borerBuprestidaeAgrilusFraxinusBiologyBotanyPopulationPEST analysisGreen leaf volatilesPopulation densityHorticulture

Abstract

fetched live from OpenAlex

The emerald ash borer, Agrilus planipennis Fairmaire (Coleoptera: Buprestidae), is a serious invasive pest of North American ash (Fraxinus spp.) that has caused devastating mortality since it was first identified in North America in 2002. In 2012, we conducted field trapping assays that tested the efficacy of purple prism and fluon-coated green multifunnel (Lindgren funnel) traps. Traps were baited with combinations of several lures that were previously shown to be attractive to A. planipennis: manuka oil--a sesquiterpene-rich oil, (3Z)-hexenol--a green leaf volatile, or (3Z)-dodecen-12-olide [= (3Z)-lactone], a sex pheromone. Eighty-nine blocks (trap lines) were tested throughout nine states along the outer edges of the currently known A. planipennis infestation in North America. Trap catch was highest on fluon-coated green multifunnel traps, and trap detections at sites with low A. planipennis population density ranged from 72 to 76% for all trap and lure types tested. (3Z)-hexenol and (3Z)-lactone baited traps functioned as well as (3Z)-hexenol and manuka oil-baited traps. Independent of the lure used, detection rates on green fluon-coated multifunnel traps were comparable with glued purple prism traps in areas with low A. planipennis population densities.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.248
Threshold uncertainty score0.394

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.248
Teacher spread0.233 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations29
Published2014
Admission routes1
Has abstractyes

Explore more

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