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Record W68208833 · doi:10.1093/jaoac/89.5.1425

Determination of Eight Synthetic Pyrethroids in Bovine Fat by Gas Chromatography with Electron Capture Detection

2006· article· en· W68208833 on OpenAlexaff
Christine Akre, James D. MacNeil

Bibliographic record

VenueJournal of AOAC International · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPesticide Exposure and Toxicity
Canadian institutionsCanadian Food Inspection Agency
Fundersnot available
KeywordsGas chromatographyChromatographyElectron capture detectorElectron captureChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Synthetic pyrethroids are among the most widely used classes of insecticides, and their uses are varied, including plant protection, animal dips, and as a treatment for human clothing and bedding in very hot climates. Veterinary applications include ear tags, pour-on formulations, sprays, and dips. Persistent residues have been reported in livestock, and routine monitoring programs in other countries have found detectable residues of various pyrethroids in fat. A method has been developed using solid-phase extraction that reduces the quantities of solvents used, the time required, and the amount of glassware used compared to an earlier method on which it was based. The scope of analytes tested included the 5 compounds cited in the earlier method (flucythrinate, permethrin, cypermethrin, fenvalerate, and deltamethrin) and, in addition, cyfluthrin, lambda-cyhalothrin, and fluvalinate. Sample extracts were analyzed by gas chromatography with electron capture detection using selected chromatographic peaks characteristic of each compound. Limits of quantification for the compounds were from 25-50 microg/kg, with a linear response for all compounds to 200 microg/kg. Recoveries ranged from 80 to 123%.

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 score0.299
Threshold uncertainty score0.136

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 head0.004
GPT teacher head0.194
Teacher spread0.190 · 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

Citations19
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueJournal of AOAC InternationalSame topicPesticide Exposure and ToxicityFrench-language works237,207