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Record W2157257592 · doi:10.1093/jat/bku072

Validation of an EMIT® Screening Method to Detect 6-Acetylmorphine in Oral Fluid

2014· article· en· W2157257592 on OpenAlexaff
Gregory G Sarris, Damon Borg, Stephanie Liao, Richard Stripp

Bibliographic record

VenueJournal of Analytical Toxicology · 2014
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicForensic Toxicology and Drug Analysis
Canadian institutionsTellabs (Canada)
Fundersnot available
KeywordsChromatographyReproducibilityChemistryImmunoassayAnalyteDetection limitMass spectrometryDilutionMedicine

Abstract

fetched live from OpenAlex

An automated assay was modified and validated to qualitatively screen for 6-acetylmorphine (6-AM) in oral fluid using the Siemens EMIT II(®) Plus 6-AM urine assay. The validation utilized an oral fluid calibrator at the currently proposed Substance Abuse and Mental Health Services Administration cutoff concentration of 4 ng/mL, as well as quality control material prepared and validated through liquid chromatography-tandem mass spectrometry. All calibrator, quality control and unknown specimens were analyzed based on the dilution and buffering system of the Quantisal(®) oral fluid collection device. Immunoassay parameters such as the pipetted sample and reagent volumes as well as photometric read times were adjusted as part of the assay modification process. Validation experiments included the determination of intra- and inter-day precision and reproducibility, limits of detection (LODs), assay selectivity, stability studies and a specimen agreement study (n = 132). The 6-AM assay performed well in all validation experiments, over multiple days and under various laboratory conditions. The LOD was determined to be 1.844 ng/mL. The assay sensitivity, specificity and overall misclassification rate were found to be 90, 100 and 6%, respectively.

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)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.283
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.091
GPT teacher head0.457
Teacher spread0.366 · 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.

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

Citations3
Published2014
Admission routes1
Has abstractyes

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