MétaCan
Menu
Back to cohort
Record W2558274900 · doi:10.1128/cmr.00010-16

Respiratory Syncytial Virus: Infection, Detection, and New Options for Prevention and Treatment

2016· review· en· W2558274900 on OpenAlexaff
Cameron Griffiths, Steven J. Drews, David Marchant

Bibliographic record

VenueClinical Microbiology Reviews · 2016
Typereview
Languageen
FieldMedicine
TopicRespiratory viral infections research
Canadian institutionsProvincial Laboratory of Public HealthUniversity of Alberta
Fundersnot available
KeywordsRespiratory systemVirusVirologyMedicinePneumovirusIntensive care medicineParamyxoviridaeImmunologyViral diseaseInternal medicine

Abstract

fetched live from OpenAlex

Respiratory syncytial virus (RSV) infection is a significant cause of hospitalization of children in North America and one of the leading causes of death of infants less than 1 year of age worldwide, second only to malaria. Despite its global impact on human health, there are relatively few therapeutic options available to prevent or treat RSV infection. Paradoxically, there is a very large volume of information that is constantly being refined on RSV replication, the mechanisms of RSV-induced pathology, and community transmission. Compounding the burden of acute RSV infections is the exacerbation of preexisting chronic airway diseases and the chronic sequelae of RSV infection. A mechanistic link is even starting to emerge between asthma and those who suffer severe RSV infection early in childhood. In this article, we discuss developments in the understanding of RSV replication, pathogenesis, diagnostics, and therapeutics. We attempt to reconcile the large body of information on RSV and why after many clinical trials there is still no efficacious RSV vaccine and few therapeutics.

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)0.001
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 score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.003

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 head0.376
GPT teacher head0.543
Teacher spread0.167 · 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

Citations590
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueClinical Microbiology ReviewsSame topicRespiratory viral infections researchFrench-language works237,207