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Record W2141917952 · doi:10.1128/aac.00878-13

Evaluation of the Carba NP Test for Rapid Detection of Carbapenemase-Producing Enterobacteriaceae and Pseudomonas aeruginosa

2013· article· en· W2141917952 on OpenAlexafffund
Nathalie Tijet, David A. Boyd, Samir N. Patel, Michael R. Mulvey, Roberto G. Melano

Bibliographic record

VenueAntimicrobial Agents and Chemotherapy · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsCanadian Science Centre for Human and Animal HealthPublic Health OntarioToronto Public Health
FundersAssociation of Medical Microbiology and Infectious Disease Canada
KeywordsEnterobacteriaceaePseudomonas aeruginosaMicrobiologyPredictive valueBiologyPseudomonadaceaeEnterobacteriaceae InfectionsPseudomonasBacterial proteinBacteriaEscherichia coliMedicineGeneBiochemistryGeneticsInternal medicine

Abstract

fetched live from OpenAlex

The Carba NP test was evaluated against a panel of 244 carbapenemase- and non-carbapenemase-producing Enterobacteriaceae and Pseudomonas aeruginosa isolates. We confirmed the 100% specificity and positive predictive value of the test, but the sensitivity and negative predictive value were 72.5% and 69.2%, respectively, and increased to 80% and 77.3%, respectively, using a more concentrated bacterial extract. False-negative results were associated with mucoid strains or linked to enzymes with low carbapenemase activity, particularly OXA-48-like, which has emerged globally in enterobacteria.

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)0.003
metaresearch head score (Gemma)0.006
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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
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 head0.012
GPT teacher head0.243
Teacher spread0.230 · 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

Citations248
Published2013
Admission routes2
Has abstractyes

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