H1N1 pandemic: clinical and epidemiologic characteristics of the Canadian pediatric outbreak
Bibliographic record
Abstract
Canada was one of the first countries affected by the 2009 influenza H1N1 pandemic with two waves - one from May to June and one from October to December. The 2009 influenza H1N1 pandemic had many unique features when compared with seasonal influenza, including the following: more than half of the affected people were children; asthma was the most significant risk factor for hospital admission; and Aboriginal and pregnant women had a higher risk of hospital admission and complications. Antiviral therapy was widely used but data did not show any effect on the pediatric population. Outbreak spread was possibly promoted from child-child and child-adult contact, and therefore the vaccination campaign targeted the pediatric population and achieved good coverage among young children (57%). Vaccination efficacy was difficult to test because of the vaccination delay. Improvement in models of prevention and treatment are urgently needed to prepare for the possible future pandemics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".