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Record W2144118295 · doi:10.1007/bf03256384

Molecular Diagnostic Assays for Detection of Viral Respiratory Pathogens in Institutional Outbreaks

2010· review· en· W2144118295 on OpenAlexaff
Nick A. Antonishyn, Paul N. Levett

Bibliographic record

VenueMolecular Diagnosis & Therapy · 2010
Typereview
Languageen
FieldMedicine
TopicRespiratory viral infections research
Canadian institutionsSaskatchewan Disease Control LaboratorySaskatchewan Health
Fundersnot available
KeywordsOutbreakBiologyVirologyIsolation (microbiology)Microbiology

Abstract

fetched live from OpenAlex

Outbreaks of viral respiratory disease in institutions may be associated with high morbidity and mortality, depending upon the viral etiology and the age and immune status of the affected patients. Control of outbreaks may include isolation and/or cohorting, and prophylaxis or treatment with specific antiviral agents may be indicated, all dependent upon the specific cause of the outbreak. Conventional methods of viral diagnosis detect only a limited number of the viruses that are known to cause outbreaks. The availability of sensitive and specific molecular assays has facilitated rapid diagnosis of a wider range of viruses from respiratory outbreaks. Molecular methods have distinct advantages over conventional methods, including the ability to rapidly develop assays for emerging viruses and new variants of existing viruses. In addition, molecular testing allows rapid detection of resistance to antiviral agents or mutations leading to increased virulence. However, high-throughput molecular testing requires batch processes that may compromise the ability to respond quickly to urgent testing demands.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.967
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.066
GPT teacher head0.389
Teacher spread0.323 · 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 teacher head, not a consensus.

Study designOther design
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

Citations4
Published2010
Admission routes1
Has abstractyes

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