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Record W2759158291 · doi:10.1093/jee/tox247

New Food Baits for Trapping German Cockroaches, Blattella germanica (L.) (Dictyoptera: Blattellidae)

2017· article· en· W2759158291 on OpenAlexafffund
Joshua Cornelis Pol, Sebastian Ibarra Jimenez, Gerhard Gries

Bibliographic record

VenueJournal of Economic Entomology · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicInsects and Parasite Interactions
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDictyopteraGerman cockroachBiologyCockroachFood scienceFermentationYeastFood spoilageSugarPEARToxicologyBotanyEcologyBiochemistryBacteria

Abstract

fetched live from OpenAlex

German cockroaches (GCRs), Blattella germanica (L.) (Dictyoptera: Blattellidae), are attracted to those beer semiochemicals (e.g., ethanol) that formerly living and active yeasts have produced or otherwise formed in the brewing process. We predicted that an earlier step in the production of beer, where yeasts actively metabolize the sugar in malted barley powder (dry malt extract [DME]), is very attractive to GCRs. In laboratory experiments, a 3-component composition (3CC) comprising DME, water, and Brewer's yeast strongly attracted GCR nymphs, females, and males. Both Brewers' yeast and 'spoilage organisms' in the DME or water seem to add to the attractiveness of the 3CC, but there is no additive or synergistic effect between them. The 3CC becomes optimally attractive to GCRs after 12 h of fermentation and stays that attractive for at least 120 h. In field trapping experiments, the 3CC and-unexpectedly-also the DME each proved as effective for attracting and capturing GCRs as a commercial cockroach bait (Combat Roach Gel). Future studies will investigate lethal biocontrol agents that can be added to the 3CC, or the DME, and will explore the efficacy of such lethal baits for GCR control.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.035
GPT teacher head0.312
Teacher spread0.277 · 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 source (direct Gemma or distilled Codex), 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

Citations13
Published2017
Admission routes2
Has abstractyes

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