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Record W2093662286 · doi:10.1080/02652030802273122

Determination of the performance characteristics of a new multi-residue method for non-steroidal anti-inflammatory drugs, corticosteroids and anabolic steroids in food animal tissues

2008· article· en· W2093662286 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFood Additives & Contaminants Part A · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPesticide Residue Analysis and Safety
Canadian institutionsCanadian Food Inspection Agency
Fundersnot available
KeywordsAnalyteAnabolismChromatographyResidue (chemistry)ChemistryDrugVeterinary drugPharmacologyMedicineBiochemistry

Abstract

fetched live from OpenAlex

A new LC-MS/MS method was developed for the analysis of 29 veterinary drug residues, spanning three different drug classes, in animal tissues. The procedures used to measure the characteristic performance parameters of the method and the results obtained using fortified blank bovine muscle and kidney tissue are described. For a quantitative and confirmatory method, the characteristic performance parameters to be determined are the limits of quantification, trueness, recovery, precision, selectivity, ruggedness, and stability. The characteristic performance parameters defined for the method will be verified during a validation study by an independent experienced analyst to determine whether the method is suitable for use in a regulatory monitoring and control program for residues of the 29 analytes.

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.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.348
Threshold uncertainty score0.361

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.024
GPT teacher head0.259
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