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Record W2087348243 · doi:10.1021/jf048414p

Determination of Five Macrolide Antibiotic Residues in Eggs Using Liquid Chromatography/Electrospray Ionization Tandem Mass Spectrometry

2005· article· en· W2087348243 on OpenAlexafffund
Jian Wang, Daniel Leung, Fred Butterworth

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2005
Typearticle
Languageen
FieldMedicine
TopicAntibiotics Pharmacokinetics and Efficacy
Canadian institutionsCanadian Food Inspection Agency
FundersCanadian Food Inspection Agency
KeywordsOleandomycinTylosinTilmicosinSpiramycinChemistryChromatographyElectrospray ionizationTandem mass spectrometrySelected reaction monitoringMass spectrometryLiquid chromatography–mass spectrometryElectrosprayErythromycinAntibiotics

Abstract

fetched live from OpenAlex

A method using liquid chromatography electrospray ionization tandem mass spectrometry (LC/ESI-MS/MS) for the determination of trace levels of five macrolide antibiotics (spiramycin, tilmicosin, oleandomycin, erythromycin, and tylosin) in eggs is presented. Data acquisition under MS/MS was achieved by applying multiple reaction monitoring (MRM) of two or three fragment ion transitions to provide a high degree of sensitivity and specificity for both quantification and confirmation. Matrix-matched standard calibration curves were used to achieve the best accuracy of the method. A fully nested experimental design was used to study the measurement uncertainty arising from intermediate precision and trueness or proportional bias. The overall recoveries, that is, those determined by the nested experiments, of spiramycin, tilmicosin, oleandomycin, erythromycin, and tylosin at fortified levels of 60, 100, 200, and 300 microg/kg were 96.8, 98.2, 98.3, 98.8, and 95.4%, respectively. The LC/ESI-MS/MS method detection limits (S/N > or = 3:1) of five macrolides were <1.0 microg/kg.

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 score0.142
Threshold uncertainty score0.333

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 head0.008
GPT teacher head0.258
Teacher spread0.250 · 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

Citations90
Published2005
Admission routes2
Has abstractyes

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