Severe Acute Respiratory Syndrome: Developing a Research Response
Bibliographic record
Abstract
When severe acute respiratory syndrome (SARS) first came to world attention in March 2003, it was immediately perceived to be a global threat with a pandemic potential. To help coordinate international research efforts, the National Institute of Allergy and Infectious Diseases convened a colloquium entitled SARS: Developing a Research Response on 30 May 2003. Breakout sessions intended to identify unmet research needs in 5 areas of SARS research--clinical research, epidemiology, diagnostics, therapeutics, and vaccines--are summarized here. Since this meeting, however, the identified research needs have been only partially met. Needs that have yet to be realized include reliable methods for early identification of individuals with SARS, a full description of SARS pathogenesis and immune response, and animal models that faithfully mimic SARS respiratory symptoms. It is also of the utmost importance that the global scientific community enhance mechanisms for international cooperation and planning for SARS research, as well as for other emerging infectious disease threats that are certain to arise in the future.
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 | 0.095 | 0.064 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.004 | 0.018 |
| Research integrity | 0.017 | 0.019 |
| Insufficient payload (model declined to judge) | 0.022 | 0.009 |
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".