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Record W2892224462 · doi:10.1128/cmr.00020-18

Methicillin-Resistant Staphylococcus aureus: Molecular Characterization, Evolution, and Epidemiology

2018· review· en· W2892224462 on OpenAlexafffund
Sahreena Lakhundi, Kunyan Zhang

Bibliographic record

VenueClinical Microbiology Reviews · 2018
Typereview
Languageen
FieldMedicine
TopicAntimicrobial Resistance in Staphylococcus
Canadian institutionsCalgary Laboratory ServicesUniversity of CalgaryAlberta Health Services
FundersCanadian Institutes of Health Research
KeywordsStaphylococcus aureusEpidemiologyMolecular epidemiologyMicrobiologyMethicillin-resistant Staphylococcus aureusStaphylococcal infectionsBiologyMedicineBacteriaGeneticsGenotypeGenePathology

Abstract

fetched live from OpenAlex

types have been discovered to date), and their classification criteria are discussed. The review then describes various typing methods applied to study the molecular epidemiology and evolutionary nature of MRSA. Starting with the historical methods and continuing to the advanced whole-genome approaches, typing of collections of MRSA has shed light on the origin, spread, and evolutionary pathways of MRSA clones.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.143
GPT teacher head0.440
Teacher spread0.297 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations1,615
Published2018
Admission routes2
Has abstractyes

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