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Record W2105247454 · doi:10.1080/02652030903013328

Validation of an optical surface plasmon resonance biosensor assay for screening (fluoro)quinolones in egg, fish and poultry

2009· article· en· W2105247454 on OpenAlex
Anne-Catherine Huet, Caroline Charlier, Stefan Weigel, Samuel Benrejeb Godefroy, Philippe Delahaut

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 · 2009
Typearticle
Languageen
FieldMedicine
TopicAntibiotics Pharmacokinetics and Efficacy
Canadian institutionsHealth Canada
FundersEuropean Commission
KeywordsSurface plasmon resonanceFish <Actinopterygii>BiosensorChemistryFisheryBiologyMaterials scienceNanotechnologyNanoparticle

Abstract

fetched live from OpenAlex

A surface plasmon resonance biosensor immunoassay has been developed for multi-residue determination of 13 (fluoro)quinolone antibiotics in poultry meat, eggs and fish. The following performance characteristics were determined according to the guidelines laid down for screening assay validation in European Decision 2002/657/EC: detection capability, specificity/selectivity, decision limit, repeatability, ruggedness and stability. The detection capability estimated for norfloxacin, the reference fluoroquinolone, was below 0.5, 1 and 1.5 ng g⁻¹ for poultry meat, egg and fish, respectively. The screening assay proved specific and showed satisfactory sensitivity below the MRL levels even though flumequine and oxolinic acid had lower cross-reactivities. A wide range of non-MRL substances were also detected at concentrations below 10 ng g⁻¹. Repeatability was good with both intra- and inter-assay coefficients of variation 56%; ruggedness was also demonstrated.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.494
Threshold uncertainty score0.706

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 head0.030
GPT teacher head0.307
Teacher spread0.277 · 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