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Record W2808118078 · doi:10.1002/anie.201804666

Maculatic Acids—Sex Attractant Pheromone Components of Bald‐Faced Hornets

2018· article· en· W2808118078 on OpenAlexafffund
Weiwu Ren, Regine Gries, Catherine S. McCaughey, Nathan Derstine, Santosh Kumar Alamsetti, Kenji L. Kurita, Lorna Tu, Roger G. Linington, Robert Britton, Gerhard Gries

Bibliographic record

VenueAngewandte Chemie International Edition · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect and Arachnid Ecology and Behavior
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOlfactometerPheromoneSex pheromoneBiologyHigh-performance liquid chromatographyBotanyZoologyChemistryChromatographyEcology

Abstract

fetched live from OpenAlex

Yellowjackets in the genera Vespula and Dolichovespula are prevalent eusocial insects of great ecological and economic significance, but the chemical signals of their sexual communication systems have defied structural elucidation. Herein, we report the identification of sex attractant pheromone components of virgin bald-faced hornet queens (Dolichovespula maculata). We analyzed body surface extracts of queens by coupled gas chromatographic-electroantennographic detection (GC-EAD), isolated the compounds that elicited responses from male antennae by high-performance liquid chromatography (HPLC), and identified these components by GC mass spectrometry (MS), HPLC-MS, and NMR spectroscopy. In laboratory olfactometer experiments, synthetic (2Z,7E)-3,7-dimethyldeca-2,7-diendioic acid (termed here maculatic acid A) and (2Z,7E)-10-methoxy-3,7-dimethyldeca-10-oxo-deca-2,7-dienoic acid (termed here maculatic acid C) in binary combination significantly attracted bald-faced hornet males. These are the first sex attractant pheromone components identified in yellowjackets.

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 head0.019
GPT teacher head0.274
Teacher spread0.255 · 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

Citations6
Published2018
Admission routes2
Has abstractyes

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