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Bibliographic record
Abstract
A serosurvey conducted in a sample of first quarter pregnant women in France at week 48-49 of 2009 exhibit a seroprevalence level of 10.6%. It has been extrapolated in male and female population living in France mainland, aged 20-39 yr, that 1,712,000, 95%CI (1,112,700 – 2,311,300) people were recently infected by H1N1pdm (recently vaccinated women were excluded from analysis). From week 36 to 46-47 of 2009, 336,288, 95%CI (207,303-421,299) patients visited their general practitioners with clinical influenza in France, mainland. We then extrapolated the proportion of symptomatic H1N1pdm influenza in both males and females aged 20-39 yr who visited their GP to be 19.6%. Surprisingly, 8 months after having alerted at a global level for H1N1pdm, there is still no published data on seroprevalence in any countries. Therefore, there is still no published estimation of the proportion of asymptomatic infections due to the pandemic strain. We have launched in France a weekly repeated seroprevalence survey in pregnant women who were volunteers to give their blood for H1N1pdm hemagglutination inhibition (HI) serosurvey during their first term of their pregnancy [1]. By comparing our data to cumulated figures of incident cases of clinical influenza provided by the French Sentinelles system [2] we provide estimate of the proportion of patients
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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 | 0.007 | 0.083 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.527 | 0.454 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".