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Record W2001290220 · doi:10.1021/jf9010005

Quantitative Screening of Stilbenes and Zeranol and Its Related Residues and Natural Precursors in Veal Liver by Gas Chromatography−Mass Spectrometry

2009· article· en· W2001290220 on OpenAlexaff
Leslie C. Dickson, Roderick Costain, Del McKenzie, Adrian C E Fesser, James D. MacNeil

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2009
Typearticle
Languageen
FieldChemistry
TopicAnalytical Chemistry and Chromatography
Canadian institutionsCanadian Food Inspection Agency
Fundersnot available
KeywordsZeranolChemistryChromatographyMass spectrometryGas chromatographyHexestrolGas chromatography–mass spectrometryAnalyteDetection limitDiethylstilbestrolBSTFAQuantitative analysis (chemistry)BiochemistryInternal medicineHormone

Abstract

fetched live from OpenAlex

An existing gas chromatography-mass spectrometry-based quantitative screening method for the regulatory analysis of the resorcylic acid lactones zeranol, taleranol, and zearalanone and the stilbene anabolic steroids diethylstilbestrol and dienestrol was extended to include natural precursors of zeranol (zearalenone, alpha-zearalenol, and beta-zearalenol) in veal liver. No changes in sample preparation were required; the instrumental conditions were selected to effect a suitable chromatographic separation and detection of the analytes. Validation experiments were performed to verify the performance and applicability of the extended method for the quantitative screening of the original and additional analytes in veal liver in the concentration range from 0.5 to 2.0 microg/kg. The limits of detection were 0.08-0.19 microg/kg. The limits of quantitation were 0.27-0.64 microg/kg. Recoveries were 29-67%. Combined relative measurement uncertainty estimates were 6-21%.

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 score0.078
Threshold uncertainty score0.787

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 integrity0.0000.001
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 head0.006
GPT teacher head0.208
Teacher spread0.201 · 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

Citations22
Published2009
Admission routes1
Has abstractyes

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