Bibliographic record
Abstract
This scan of the literature was undertaken on behalf of the Public Health of Canada (PHAC). It formed the basis for and accompanies the report on Hepatitis C Virus (HCV), titled: “Hepatitis C: Strategic Issues towards a Global Awareness Campaign. ” The report was prepared as a result of the concern of PHAC that issues related to HCV have not received sufficient global recognition. As a result of the lack of sufficient resources and attention, the progress in tackling the disease has been uneven and sporadic, and, it has been termed as a ‘silent epidemic.’ The focus of attention in this survey is on the issues of prevalence, epidemiology, and public health policies in the developing countries. However, important and relevant research from the developed (or OECD) countries has been included for comparitive purposes. The literature scan seved to provide a basis for the report to PHAC on the need for increased global awareness (see above). It is the aim of PHAC to use these outputs towards further consultation with stakeholders. The report and the literature scan will also be used for discussions at a workshop at the 13 th Canadian Conference on International Health (CCIH) organised jointly by PHAC and the Canadian Society for International Health (CSIH) in October 2006. 2 Bibliography Agence Nationale d'Accréditation et d'Évaluation en Santé (ANAES). “Depistage de
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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 | 0.002 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.341 | 0.159 |
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".