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Record W2051215861 · doi:10.1002/ps.929

Chemical residues and bioactivity of tebufenozide applied to apple foliage

2004· article· en· W2051215861 on OpenAlexaffabout
Michael J. Smirle, D. Thomas Lowery, Cheryl L. Zurowski

Bibliographic record

VenuePest Management Science · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect and Pesticide Research
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsInsect growth regulatorBioassayToxicologyResidue (chemistry)PesticideChemistryBiologyAnimal scienceBotanyLarvaAgronomyEcologyBiochemistry

Abstract

fetched live from OpenAlex

Abstract Tebufenozide, an insect growth regulator that acts as an ecdysone agonist, was applied at recommended label rate to apple trees in August 1997 and May 1998. Foliar residues were determined by high‐performance liquid chromatography from samples collected 2, 24, 48 and 96 h post‐spray, and at weekly intervals thereafter for 9 weeks in 1997 and 11 weeks in 1998. Foliage sampled at the same times was used in bioassays to determine residual toxicity to first‐instar obliquebanded leafrollers, Choristoneura rosaceana (Harris). Residue decay followed first‐order kinetics in both years, with residual half‐life of 36.3 days in 1997 and 7.2 days in 1998. Estimates of the time needed to reduce bioactivity to 50% in bioassays were 18.7 days in 1997 and 36.3 days in 1998. The accuracy of equations describing decay of tebufenozide residues and bioactivity over time was not improved by using degree‐day accumulations as the independent variable. For the Department of Agriculture and Agri‐Food, Government of Canada, © Minister of Public Works and Government Services Canada 2004. Published for SCI by John Wiley & Sons, Ltd.

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 score0.008
Threshold uncertainty score0.016

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 head0.254
Teacher spread0.235 · 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

Citations16
Published2004
Admission routes2
Has abstractyes

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