TECHNICAL ADVANCE An update of “Cost-effecti l c
Bibliographic record
Abstract
ct av us ca ing on the disease's epidemiology and on the observed indirect protection (herd immunity) after the introduc-more favorable than previously calculated in several studies [1,6,7,10,11]. In addition to epidemiological Tu et al. BMC Infectious Diseases 2013, 13:54 http://www.biomedcentral.com/1471-2334/13/54forced results of other studies on the topic [8,15-20]. ItInstitute of Health Policy, Management and Evaluation, University of Toronto, Ontario, Canadation of the vaccine have been carried out in other coun-tries. In particular, there have been studies on the etiology of acute gastroenteritis in hospitalized children in the Netherlands [2,3]. In these studies, the incidence and relevance of rotavirus reported a national number exceeding 5,000 hospitalized rotavirus gastroenteritis studies of rotavirus-related disease, studies on the observed indirect protection (herd immunity) have been carried out either through observing the actual change in RVGE hospitalized cases in the US [8,12] between pre and post- rotavirus vaccination eras or through pro-jecting the impacts of rotavirus vaccination by applying mathematical transmission models in England and Wales [13] or in five other countries in the European Union [14]. The results from these studies have rein- * Correspondence: thihonganh.tu@utoronto.ca†Equal contributorsConclusions: We concluded that the results on potentially favourable cost-effectiveness in the previous study remained valid, however, the new data suggested that previous results might represent an underestimation of the economic attractiveness of rotavirus vaccination.
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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 | 0.011 | 0.062 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.107 | 0.029 |
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".