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Record W2753820868 · doi:10.1097/olq.0000000000000707

A Comparison of Real-Time Polymerase Chain Reaction Assays for the Detection of Antimicrobial Resistance Markers and Sequence Typing From Clinical Nucleic Acid Amplification Test Samples and Matched Neisseria gonorrhoeae Culture

2017· article· en· W2753820868 on OpenAlexaff
Shelley Peterson, Irene Martín, Walter Demczuk, Linda Hoang, John Wylie, Brigitte Lefebvre, Annie‐Claude Labbé, Prenilla Naidu, David Haldane, Michael R. Mulvey

Bibliographic record

VenueSexually Transmitted Diseases · 2017
Typearticle
Languageen
FieldImmunology and Microbiology
TopicReproductive tract infections research
Canadian institutionsProvincial Laboratory of Public HealthQueen Elizabeth II Health Sciences CentreUniversité de MontréalSte. Anne's HospitalBC Centre for Disease ControlPublic Health Agency of Canada
Fundersnot available
KeywordsNeisseria gonorrhoeaeNucleic Acid Amplification TestsPolymerase chain reactionTypingNeisseriaMicrobiologyNucleic acidMedicineVirologyReal-time polymerase chain reactionNeisseriaceaeBiologyGeneticsBacteriaGeneAntibioticsChlamydia trachomatis

Abstract

fetched live from OpenAlex

Real-time polymerase chain reaction (PCR) assays to detect antimicrobial resistance-associated mutations were tested on Neisseria gonorrhoeae-positive clinical samples with matched isolates. Of the nucleic acid amplification tests/cultures, 87.7% (64/73), 98.6% (72/73), and 98.4% (62/63) predicted cephalosporin, ciprofloxacin, and azithromycin susceptibilities, respectively. N. gonorrhoeae multiantigen sequence type was correctly predicted for 98.7% (79/80), and 13 of 58 N. gonorrhoeae-negative specimens showed false-positive results.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.021
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.050
GPT teacher head0.355
Teacher spread0.305 · 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 source (direct Gemma or distilled Codex), 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

Citations10
Published2017
Admission routes1
Has abstractyes

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