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Record W4414182692 · doi:10.1111/eea.70013

Effects of Collection Cup Preservative on Flight Intercept Trap Performance for Forest Insects

2025· article· en· W4414182692 on OpenAlexafffund
Joel T.L. Goodwin, Sandy M. Smith, Jeremy D. Allison

Bibliographic record

VenueEntomologia Experimentalis et Applicata · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsToronto and Region Conservation AuthorityNatural Resources CanadaCanadian Forest Service
FundersCanadian Forest ServiceNatural Sciences and Engineering Research Council of CanadaU.S. Forest ServiceNatural Resources CanadaUniversity of Toronto
KeywordsAbundance (ecology)Trap (plumbing)Pitfall trapPreservativeMark and recaptureData collectionPheromone trapPheromone

Abstract

fetched live from OpenAlex

ABSTRACT Flight intercept traps are important tools for the monitoring and surveillance of forest Coleoptera. Although collection cup effects on the abundance of target taxa are well‐documented, these effects remain poorly understood. Here, we investigated the comparative efficacy of three wet (saturated saltwater, propylene glycol, and soapy water) and one dry (dichlorvos strip) collection cup treatments on the capture of forest insects. We observed significant differences in capture rates across treatments, with wet cups generally resulting in higher captures of phytophagous and predatory taxa. Dry cups captured the largest quantities of carrion‐associated taxa. These findings challenge the prevailing hypothesis of insect escape from dry collection cups and suggest that olfactory stimuli associated with collection cups are important in mediating trap performance. Despite these insights, the specific mechanisms driving these preferences remain unknown and should be the focus of future research.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.334
Threshold uncertainty score0.777

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 head0.010
GPT teacher head0.278
Teacher spread0.267 · 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 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

Citations0
Published2025
Admission routes2
Has abstractyes

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