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Record W2105403405 · doi:10.1086/420743

Severe Acute Respiratory Syndrome

2004· review· en· W2105403405 on OpenAlexaff
Susan M. Poutanen, Mona Loutfy, Matthew Muller, D. E. Low

Bibliographic record

VenueClinical Infectious Diseases · 2004
Typereview
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsUniversity of TorontoMount Sinai HospitalToronto General HospitalMcGill UniversityUniversity Health Network
Fundersnot available
KeywordsEpidemiologyCoronavirusMedicineRespiratory systemSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Intensive care medicineRespiratory illnessPresentation (obstetrics)Coronavirus disease 2019 (COVID-19)Severe acute respiratory syndrome coronavirusSevere acute respiratory syndromeVirologyPediatricsInternal medicineDiseaseSurgery

Abstract

fetched live from OpenAlex

The first cases of severe acute respiratory syndrome (SARS) occurred in China in November 2002. The agent causing this illness has been identified as a novel coronavirus, SARS-coronavirus. Since its introduction <1 year ago, this virus has infected 8098 people in 26 countries, killing 774 of them. We present an overview of the epidemiology, clinical presentation, diagnosis, and treatment of SARS based on the current state of knowledge derived from published studies and our own personal experience.

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 score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.006

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 head0.138
GPT teacher head0.487
Teacher spread0.350 · 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

Citations221
Published2004
Admission routes1
Has abstractyes

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