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Record W2098534796 · doi:10.1586/14787210.3.2.251

Overview of antiviral and anti-inflammatory treatment for severe acute respiratory syndrome

2005· review· en· W2098534796 on OpenAlexaff
Stephen Chihrin, Mona Loutfy

Bibliographic record

VenueExpert Review of Anti-infective Therapy · 2005
Typereview
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsNorth York General HospitalWestern University
Fundersnot available
KeywordsOutbreakMedicineMiddle East respiratory syndromeIntensive care medicineSurpriseDiseasePublic healthMainland ChinaVirusCoronavirus disease 2019 (COVID-19)ImmunologyVirologyInfectious disease (medical specialty)ChinaInternal medicinePathologyPolitical science

Abstract

fetched live from OpenAlex

In 2003, an outbreak of a novel respiratory virus exploded from mainland China into an international issue, catching the world by surprise. The ensuing challenges to hospital and public health workers rose to a level never before seen in healthcare, in part due to the unknown nature of the disease, the fear of the human-to-human transmission and the significant media involvement. A new coronavirus was identified as the causative agent and named the severe acute respiratory syndrome-associated virus. A number of antiviral and anti-inflammatory treatment strategies were explored during the epidemic, with varying success. Following the epidemic, in vitro antiviral analyses of numerous compounds have been conducted. This review summarizes treatment agents assessed during and after the 2003 severe acute respiratory syndrome outbreak, with the aim of guiding future decision makers should the virus return.

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: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.003

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 head0.105
GPT teacher head0.453
Teacher spread0.348 · 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 designSystematic review
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

Citations22
Published2005
Admission routes1
Has abstractyes

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