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Record W2588968442

Web: SARS Reference

2003· article· en· W2588968442 on OpenAlexaboutno aff
James Maskalyk

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Outbreaks Research
Canadian institutionsnot available
Fundersnot available
KeywordsChinaSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)EpidemiologyMultinational corporationComputer scienceCoronavirus disease 2019 (COVID-19)MedicineOutbreakWorld Wide WebPolitical scienceVirologyLawPathology
DOInot available

Abstract

fetched live from OpenAlex

On 6 June 2003, as has become my habit, I glanced at the World Health Organization's global epidemic curve for severe acute respiratory syndrome (SARS). With infection control procedures finally taking hold in China, the shape of the curve was moving downwards and approximating the bell shape so cleanly described in epidemiology textbooks. The relative brevity of the bell for the 21st century's first major epidemic can be attributed to an aspect of 21st century medicine that had never before been tested so singularly, and completely: multinational collaboration, real time epidemiological updates, and online medical publication all made possible through digital connections. The speed with which data, experience, successes, and failures were shared appears to have slowed the epidemic. The recent spate of online SARS offerings has provided more than graphs and data: it has also given us a SARS textbook. SARS Reference intends to summarise information on the SARS outbreak each month for the duration of the epidemic. The first edition, covering information available since the outbreak began in November 2002 and current as of 6 May 2003, was written over 14 days by a group of volunteers and posted at SARSreference.com on 8 May 2003. So far, it has been translated into Chinese and Spanish, and the editors promise to release copyright to individuals who are willing to translate it into other languages. They report that there is currently no sponsorship for the site, nor would any be accepted. SARS Reference is a comprehensive summary of what we know to date. It is well organised into nine chapters, from the epidemiology of outbreaks in different countries to SARS in children. Each is available in printable format, and extensively referenced. The strongest sections are those on virology and diagnostic testing. Sections on transmission/prevention and case definition rely heavily on recommendations from the US Centers for Disease Control and WHO, with some support from the published literature. Both for SARS medicine and for online publishing, this is an important step forward. Its greatest strengths are its comprehensive review of the literature, an abundance of links to authoritative internet sites, and refreshingly clear writing. Unfortunately, there is no mention of peer review and no assurance that the information offered is accurate enough to guide appropriate management of a group of SARS patients. Further, as evidence of varying quality accumulates, and changes from observational to experimental, the task of synthesising and summarising it will be less easy, and will require critical analysis that is not offered here. Clicking on WHO's website, I opened the epidemiological curve for Toronto, my home. It also showed a nice bell curve. Two of them, actually, and the second seemed not quite done. Apparently, there are lessons that this disease has yet to teach us, and for the time being, there seems no better record than SARSreference.com

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.070
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0070.004
Open science0.0030.003
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.9300.942

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 head0.074
GPT teacher head0.374
Teacher spread0.301 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2003
Admission routes1
Has abstractyes

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