Pandemic 2009 (A)H1N1 influenza (swine flu) — the Manitoba experienceThis paper is one of a selection of papers published in this special issue entitled “Second International Symposium on Recent Advances in Basic, Clinical, and Social Medicine” and has undergone the Journal's usual peer review process.
Bibliographic record
Abstract
The pattern of illness associated with the first wave of the pandemic influenza A H1N1 (swine flu) in the spring and early summer of 2009 in regions of the province of Manitoba in Canada was more severe, on a population basis, than any other northern hemisphere jurisdiction outside of Mexico City. Manitoba accounted for 50% of intensive care admissions and 25% of pediatric admissions, but only 6.5% of deaths, attributable to the virus in Canada during the first wave. Activation and use of emergency response protocols embedded within the routine health authority management system and good communication between the diagnostic laboratory, public health, and health care practitioners was effective in coping with the sudden need for hospitalization of large numbers of children and young adults with severe respiratory illness over a short time period. Early treatment with oseltamivir was associated with a shorter duration of hospitalization among children. Intensive education of health care providers, patients, and visitors, along with close monitoring of infection prevention and control practices, were instrumental in preventing both nosocomial and health care worker infections.
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 | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".