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Record W2127769113 · doi:10.1111/imb.12053

Odorant receptors of a primitive hymenopteran pest, the wheat stem sawfly

2013· article· en· W2127769113 on OpenAlexaboutno aff
Joanna C. Gress, Hugh M. Robertson, David K. Weaver, Mensur Dlakić, Kevin W. Wanner

Bibliographic record

VenueInsect Molecular Biology · 2013
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology and Insect Physiology Research
Canadian institutionsnot available
Fundersnot available
KeywordsSawflyBiologyPEST analysisIntegrated pest managementHymenopteraInsectOlfactionBotanyZoologyEvolutionary biologyEcology

Abstract

fetched live from OpenAlex

The wheat stem sawfly, Cephus cinctus, is an herbivorous hymenopteran that feeds exclusively on members of the Graminae family. Synanthropically, it has become one of the most important insect pests of wheat grown in the northern Great Plains region of the USA and Canada. Insecticides are generally ineffective because of the wheat stem sawfly's extended adult flight period and its inaccessible larval stage, during which it feeds within the wheat stems, making it virtually intractable to most pest management strategies. While research towards integrated pest management strategies based on insect olfaction has proved promising, nothing is known about the molecular basis of olfaction in this important pest species. In this study we identified 28 unique odorant receptor (Or) transcripts from an antennal transcriptome. A phylogenetic analysis with the predicted Ors from the honey bee and jewel wasp genomes revealed at least four clades conserved amongst all three Hymenoptera species. Antennal expression levels were analysed using quantitative real-time PCR, and one male-biased and five female-biased Ors were identified. This study provides the basis for future functional analyses to identify behaviourally active odours that can be used to help develop olfactory-mediated pest management tools.

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)0.0000.000

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 head0.032
GPT teacher head0.286
Teacher spread0.253 · 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

Citations14
Published2013
Admission routes1
Has abstractyes

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