Severe acute respiratory syndrome (SARS)
Bibliographic record
Abstract
In the second week of March of this year, the World Health Organization (WHO) received reports of >150 cases of acute respiratory illness associated with pneumonia 1. The majority of these cases were from the South-East Asian countries of China (including Hong Kong), Vietnam, Indonesia, the Philippines and Singapore. The appearance of many cases over a short time period, the absence of a clear causative pathogen, the apparent spread between countries and the death of some cases led to the issue of a global alert. The subsequent increase in the number of cases in this region and the identification of possible cases in distant countries, such as Germany, Canada and the UK (table 1⇓), increased alarm that a transmissible agent was causing an epidemic that was being further spread by easy access to air travel. Alarm was fed by the prior report of the deaths of two members of a family from Hong Kong with H5 N1 influenza virus infection presumed to have been acquired from birds on the Chinese mainland and the reporting of an earlier outbreak of respiratory infection of unknown cause in the Guangdong Province in China that had affected >300 individuals of whom three died. View this table: Table 1 Cumulative number of reported cases of severe acute respiratory syndrome (SARS) to March 29 2003 The WHO took a pivotal role in the investigation of the outbreak, with the development of a case definition for severe acute respiratory syndrome (SARS) (fig. 1⇓) 1. Global Outbreak Alert and Response teams assisted in outbreak management and the collection of epidemiological and clinical data to improve the understanding of the condition. A …
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.008 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".