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Record W2142016681 · doi:10.1139/z04-075

Carbon stable isotopes: a tool for studying the mating, oviposition, and spatial distribution of races of European corn borer, <i>Ostrinia nubilalis</i>, among host plants in the field

2004· article· en· W2142016681 on OpenAlexvenueno aff
S. Ponsard, Arnaud Bontemps, Laurent Pélozuelo, Denis Bourguet

Bibliographic record

VenueCanadian Journal of Zoology · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsOstriniaBiologyEuropean corn borerLepidoptera genitaliaCrambidaeHost (biology)Ostrinia furnacalisPyralidaeBotanyPEST analysisAgronomyEcology

Abstract

fetched live from OpenAlex

The European corn borer, Ostrinia nubilalis (Hübner, 1796) (Lepidoptera: Crambidae), is a polyphagous corn pest species that includes two host races: one feeding on corn (Zea mays L.) and one feeding on mugwort (Artemisia vulgaris L.) and hop (Humulus lupulus L.). Being able to determine the type of host plant on which field-caught moths fed as larvae would allow for the quantification of mating rates within and between races, as well as the quantification of the spatial distribution and oviposition of both races in the field. We found that stable carbon isotopes (δ; 13 C) are a reliable indicator of host-plant photosynthetic type (C3 or C4) regardless of adult food and intensity of metabolism; so even when food or metabolism had a significant effect on wing δ 13 C values, the magnitude of this effect was too small to obscure the signal characterizing host-plant type. Egg and spermatophore δ 13 C values similarly reflect female and male host-plant type, respectively, regardless of adult feeding. We found 224 host-plant species of O. nubilalis in the literature, including 19 species with C4-type photosynthesis. However, in temperate areas, corn is probably the only significant C4 source of adult moths. Accordingly, wing δ 13 C values were more variable in field-caught moths showing a typical C3-type δ 13 C value than in those showing a typical C4-type δ 13 C value.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.228
Threshold uncertainty score0.960

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.007
GPT teacher head0.208
Teacher spread0.201 · 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

Citations54
Published2004
Admission routes1
Has abstractyes

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