Bibliographic record
Abstract
York Central Hospital, Richmond Hill, Ontario Correspondence and reprints: Dr Richard Schabas, York Central Hospital, 10 Trench Street, Richmond Hill, Ontario, L4C 4Z3. Telephone 905-883-1212 ext 312, fax 905-883-2455, e-mail rschabas@yorkcentral.on.ca Quarantine, the isolation of asymptomatic individuals who are thought to be incubating infection, was a prominent control strategy used in the recent severe acute respiratory syndrome (SARS) outbreaks. A recent report about the public health efforts to control SARS in Toronto concluded that in future outbreaks “for every case of SARS, health authorities should expect to quarantine up to 100 contacts” (1). This is a remarkable conclusion. It is one thing to resort to an unproven intervention in the crisis posed by a novel disease threat; however, it is quite another to recommend the continued use of this intervention after the dust has settled and we know, or should know, a great deal more about the problem at hand. Mass quarantine for disease control was essentially abandoned last century. Does it deserve a second look? An outbreak should meet the following three criteria for quarantine to be a useful measure of disease control:
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".