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Record W2140400415 · doi:10.1128/jcm.01509-06

Verification of the IDI-MRSA Assay for Detecting Methicillin-Resistant <i>Staphylococcus aureus</i> in Diverse Specimen Types in a Core Clinical Laboratory Setting

2006· article· en· W2140400415 on OpenAlexaff
Steven J. Drews, Barbara Willey, N. Kreiswirth, Min Wang, Teresa Ianes, Jayne Mitchell, Mary Latchford, Allison McGeer, Kevin Katz

Bibliographic record

VenueJournal of Clinical Microbiology · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial Identification and Susceptibility Testing
Canadian institutionsNorth York General HospitalUniversity Health NetworkUniversity of Toronto
Fundersnot available
KeywordsMethicillin-resistant Staphylococcus aureusStaphylococcus aureusMedicineClinical microbiologyMicrobiologyMicrococcaceaeStaphylococcal infectionsBiologyAntibacterial agentAntibioticsBacteria

Abstract

fetched live from OpenAlex

The IDI-MRSA assay has a sensitivity of 96% and a specificity of 96% when used to screen patients at extranasal sites. This verification study used previously unverified swabs and was undertaken in a core medical laboratory using nonmicrobiology technologists trained in sample processing, molecular laboratory work flow, and PCR practice.

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)0.005
metaresearch head score (Gemma)0.009
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 score0.005
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.049
GPT teacher head0.359
Teacher spread0.310 · 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

Citations50
Published2006
Admission routes1
Has abstractyes

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