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Record W3153958826 · doi:10.1097/olq.0000000000001360

Workflow and Throughput of Commercial Assays to Detect Mycoplasma genitalium and Macrolide Resistance–Mediating Mutations

2021· article· en· W3153958826 on OpenAlexaff
Anika Shah, Dan Jang, Irene Martín, David J. Speicher, Ravinder Lidder, Avery Clavio, Sam Ratnam, Marek Smieja, Max Chernesky

Bibliographic record

VenueSexually Transmitted Diseases · 2021
Typearticle
Languageen
FieldImmunology and Microbiology
TopicReproductive tract infections research
Canadian institutionsPublic Health Agency of CanadaMcMaster UniversitySt. Joseph’s Healthcare Hamilton
Fundersnot available
KeywordsMycoplasma genitaliumMedicineMicrobiologyMycoplasmaMutationVirologyGeneticsGeneBiologyChlamydia trachomatis

Abstract

fetched live from OpenAlex

ABSTRACT: Aptima Mycoplasma genitalium (MG) required the shortest and STD6 the longest time to detect MG in clinical samples. ResistancePlus MG detected MG and macrolide resistance-mediating mutations simultaneously. Times were influenced by specimen numbers. M. genitalium positives from the other 2 assays required increased time for macrolide resistance-mediating mutation sequencing.

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)0.007
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.008
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.008
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.001
Science and technology studies0.0010.001
Scholarly communication0.0040.001
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.008

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 head0.013
GPT teacher head0.278
Teacher spread0.265 · 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 designObservational
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

Citations1
Published2021
Admission routes1
Has abstractyes

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