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Record W2177158543 · doi:10.1093/jee/96.3.879

Susceptibility of Leafrollers (Lepidoptera: Tortricidae) from Organic and Conventional Orchards to Azinphosmethyl, Spinosad, and Bacillus thuringiensis

2003· article· en· W2177158543 on OpenAlexaff
Michael J. Smirle, D. Thomas Lowery, Cheryl L. Zurowski

Bibliographic record

VenueJournal of Economic Entomology · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect Resistance and Genetics
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsTortricidaeLepidoptera genitaliaBiologySpinosadBacillus thuringiensisBotanySex pheromonePesticideEcology

Abstract

fetched live from OpenAlex

Populations of obliquebanded leafroller, Choristoneura rosaceana Harris, and three-lined leafroller, Pandemis limitata Robinson, were obtained from seven sites in the Okanagan and Similkameen Valleys of British Columbia and assayed for their responses to three insecticides using a leaf disk bioassay. Lethal concentration ratios (LCRs) were calculated for all populations compared with a susceptible laboratory colony of C. rosaceana; significant variation was detected in response to all three insecticides. LCRs were 0.86-15.52 for azinphosmethyl, 0.38-2.37 for spinosad (Success), and 0.58-4.89 for Bacillus thuringiensis (Foray). Correlation analysis indicated no cross-resistance among the three insecticides. Leafroller populations obtained from apple orchards managed with organic production practices were more susceptible to azinphosmethyl than leafrollers obtained from conventionally managed sites. Conversely, the highest levels of tolerance to B. thuringiensis were observed in the populations from organic sites, possibly reflecting usage patterns; B. thuringiensis is one of the few insecticides allowed under organic production guidelines. All populations were highly susceptible to spinosad, which may be a useful tool for resistance management programs if used judiciously.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.466

Codex and Gemma teacher scores by category

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 head0.010
GPT teacher head0.246
Teacher spread0.236 · 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 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

Citations24
Published2003
Admission routes1
Has abstractyes

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