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Record W2944095488 · doi:10.1093/jee/toz095

Determining Temperature-Dependent Development and Mortality Parameters of the Swede Midge (Diptera: Cecidomyiidae)

2019· article· en· W2944095488 on OpenAlexafffundabout
Jenny Liu, Boyd A. Mori, O. Olfert, Rebecca H. Hallett

Bibliographic record

VenueJournal of Economic Entomology · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect behavior and control techniques
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of Guelph
FundersCanola Council of Canada
KeywordsCecidomyiidaeBiologyMidgeToxicologyEcologyLarva

Abstract

fetched live from OpenAlex

The swede midge (Contarinia nasturtii Kieffer) is an invasive insect in North America whose feeding has caused a decline of over 60% of total canola acreage in Ontario, Canada since 2011. Temperature-dependent development and mortality information are important to develop an effective pest management strategy for this insect; as the most comprehensive study on C. nasturtii development was completed on populations from the United Kingdom in the 1960s, new geographically relevant information is needed. Contarinia nasturtii eggs, larvae, pupae, and adults were reared from wild populations collected from Elora, Ontario, and allowed to develop at different temperatures. Resulting development rates were fit to a series of growth models and the model with the best relative goodness-of-fit was selected to represent the given life stage. Eggs from Ontario populations developed more quickly than their UK counterparts at temperatures below approximately 17°C, but more slowly at temperatures above 17°C. The same phenomenon was observed in larvae at 20°C. Pupae from both populations had similar development rates, and adult longevity was similar as well. This information will inform the management of C. nasturtii, and may help prevent its spread to other canola-producing regions of North America.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.022
GPT teacher head0.246
Teacher spread0.224 · 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

Citations5
Published2019
Admission routes3
Has abstractyes

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