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Record W2520825728 · doi:10.22543/0090-0222.2089

Mating Frequency of European Corn Borer (Lepidoptera: Crambidae) in Minnesota, Kansas, and Texas

2018· article· en· W2520825728 on OpenAlexaboutno aff
J. L. Hinton, David A. Andow

Bibliographic record

VenueThe Great Lakes Entomologist · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect Resistance and Genetics
Canadian institutionsnot available
FundersCooperative State Research, Education, and Extension ServiceValparaiso UniversityU.S. Department of Agriculture
KeywordsCrambidaeBiologyOstriniaLepidoptera genitaliaMatingEuropean corn borerPyralidaePopulationZoologyEcologyDemography

Abstract

fetched live from OpenAlex

The frequency of mating and polyandry in natural populations are important parameters for understanding evolutionary dynamics. Mating frequency among natural populations of Ostrinia nubilalis (Hübner) [Lepidoptera: Crambidae] are quite variable. Showers et al. (1974) found 91.1, 73.8, and 71.3% of females had mated during the second flight over 1971-3 at one location in Iowa. During 1971, only 10% mated multiple times, with lower levels of polyandry in subsequent years. In an earlier study in Iowa, Pesho (1961) found that 65-100 % of females had mated and up to 43% had mated more than once. A population in southwestern Ontario averaged 73% mating and 37% polyandry for the 5-year period from 1971-5, a higher rate of polyandry than during the same period in Iowa (Elliot, 1977). In this note, we amplify these previously published results by reporting the mating status of female O. nubilalis captured in light traps in Minnesota, Kansas and Texas. We also provide evidence that some females in natural populations may be sperm-limited.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.134
Threshold uncertainty score0.267

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.013
GPT teacher head0.244
Teacher spread0.231 · 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 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

Citations7
Published2018
Admission routes1
Has abstractyes

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