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Record W2904351021 · doi:10.1128/cmr.00042-18

Practical Guidance for Clinical Microbiology Laboratories: Viruses Causing Acute Respiratory Tract Infections

2018· review· en· W2904351021 on OpenAlexaff
Carmen Charlton, Esther Babady, Christine C. Ginocchio, Todd F. Hatchette, Robert C. Jerris, Yan Li, Mike J. Loeffelholz, Yvette S. McCarter, Melissa B. Miller, Susan Novak-Weekley, Audrey N. Schuetz, Yi‐Wei Tang, R Widen, Steven J. Drews

Bibliographic record

VenueClinical Microbiology Reviews · 2018
Typereview
Languageen
FieldMedicine
TopicRespiratory viral infections research
Canadian institutionsUniversity of ManitobaPublic Health Agency of CanadaNova Scotia Health AuthorityDalhousie UniversityProvincial Laboratory of Public HealthUniversity of Alberta
FundersNational Cancer Institute
KeywordsIntensive care medicineRespiratory tract infectionsClinical microbiologyInfectious disease (medical specialty)MedicineDiseaseImmunologyBiologyMicrobiologyRespiratory systemPathologyInternal medicine

Abstract

fetched live from OpenAlex

, published in 1986. The scope of the original document was quite broad, with an emphasis on clinical diagnosis of a wide variety of infectious agents and laboratory focus on antigen detection and viral culture. The new PGCM document is designed to be used by laboratorians in a wide variety of diagnostic and public health microbiology/virology laboratory settings worldwide. The article provides guidance to a rapidly changing field of diagnostics and outlines the epidemiology and clinical impact of acute respiratory viral infections, including preferred methods of specimen collection and current methods for diagnosis and characterization of viral pathogens causing acute respiratory tract infections. Compared to the case in 1986, molecular techniques are now the preferred diagnostic approaches for the detection of acute respiratory viruses, and they allow for automation, high-throughput workflows, and near-patient testing. These changes require quality assurance programs to prevent laboratory contamination as well as strong preanalytical screening approaches to utilize laboratory resources appropriately. Appropriate guidance from laboratorians to stakeholders will allow for appropriate specimen collection, as well as correct test ordering that will quickly identify highly transmissible emerging pathogens.

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)0.008
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: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0100.015

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 head0.552
GPT teacher head0.627
Teacher spread0.075 · 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

Citations190
Published2018
Admission routes1
Has abstractyes

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