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Record W2949525032 · doi:10.4039/tce.2019.21

Diel patterns of emergence and reproductive behaviour in the invasive swede midge (Diptera: Cecidomyiidae)

2019· article· en· W2949525032 on OpenAlexaffabout
Elisabeth A. Hodgdon, Rebecca H. Hallett, Chase A. Stratton, Yolanda H. Chen

Bibliographic record

VenueThe Canadian Entomologist · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect Pheromone Research and Control
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsCecidomyiidaeMidgeSex pheromoneMating disruptionBiologyPEST analysisDiel vertical migrationPheromoneMatingPheromone trapIntegrated pest managementEcologyBotanyLarva

Abstract

fetched live from OpenAlex

Abstract Swede midge ( Contarinia nasturtii (Kieffer); Diptera: Cecidomyiidae) is a serious invasive pest of Brassica Linnaeus (Brassicaceae) oilseed and vegetable crops in Canada and the United States of America. Pheromone mating disruption is a promising new tactic for managing this difficult pest, but research is needed to determine how pheromone delivery can be optimised. With an understanding of swede midge diel mating patterns, pest managers could limit pheromone release to periods when midges are sexually active. We conducted a series of 24-hour trials to test whether swede midge exhibit diel periodicity of emergence, female calling, and male capture in pheromone traps. We found that females began releasing pheromones almost immediately following emergence within the first five hours after dawn. In the field, we found that males were most active from dawn until late morning, indicating that midges mate primarily during the first five hours of photophase. Low levels of reproductive activity during midday and nighttime hours present opportunities to turn off dispensers and reduce the cost of pheromone inputs in a swede midge mating disruption system.

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 score0.316
Threshold uncertainty score0.416

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 head0.018
GPT teacher head0.227
Teacher spread0.209 · 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

Citations4
Published2019
Admission routes2
Has abstractyes

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