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Record W2160509084 · doi:10.1603/ec14094

Type of Intercept Trap Not Important for Capturing Female <I>Sirex noctilio</I> and <I>S. nigricornis</I> (Hymenoptera: Siricidae) in North America

2014· article· en· W2160509084 on OpenAlexafffund
Laurel J. Haavik, Elder Batista, Kevin J. Dodds, Wood Johnson, James R. Meeker, Taylor Scarr, Jeremy D. Allison

Bibliographic record

VenueJournal of Economic Entomology · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect and Pesticide Research
Canadian institutionsCanadian Forest ServiceOntario Forest Research InstituteMinistry of Natural Resources and ForestryNatural Resources Canada
FundersU.S. Forest ServiceCanadian Food Inspection AgencyNatural Resources CanadaMinistry of Natural ResourcesAnimal and Plant Health Inspection ServiceNew York State Department of Environmental ConservationU.S. Department of Agriculture
KeywordsTrap (plumbing)HymenopteraBiologyZoologyEcologyGeography

Abstract

fetched live from OpenAlex

Current detection tools for Sirex noctilio F. (Hymenoptera Siricidae) in North America are poor. To determine the importance of intercept trap type for capturing females of S. noctilio and its native congener, Sirex nigricornis F., in eastern North America, we report on seven trap comparison studies from different years and geographic locations. Among studies, total numbers of S. noctilio captured were low (mean of < or = 1 wasp per trap). Total numbers of S. nigricornis caught were generally greater, and ranged from a mean of 1-13 wasps per trap. Nearly all studies found no significant differences among intercept trap types in the number of woodwasps caught. For future studies, we recommend that either panel or 12-unit Lindgren funnel traps be used to catch S. noctilio or S. nigricornis in eastern North America.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.824
Threshold uncertainty score0.891

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.033
GPT teacher head0.270
Teacher spread0.237 · 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

Citations9
Published2014
Admission routes2
Has abstractyes

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