Modifications in the Revised National Tuberculosis Control Program to achieve universal access to tuberculosis care
Bibliographic record
Abstract
Global Tuberculosis Report - 2012, released by the World Health Organization (WHO) has revealed that in the year 2011 alone, 11.7 million new cases of tuberculosis (TB) have been reported worldwide, of which India contributed to almost one-quarter of the cases. Considering the global distribution, magnitude of the problem, serious impact on the quality of life, and high mortality rates; TB in today′s world is the biggest public health disease of an infectious nature. Revised National Tuberculosis Control Program (RNTCP) has been geographically scaled-up and updated on multiple fronts based on the epidemiology of disease, infield practical experience, WHO′s recommendations, and the successful implementation of different strategies in high burden countries. Refinement in the program has been observed in different fields such as diagnostics, treatment, involvement of medical college and private sector, along with some innovative measures. To conclude, strengthening of the RNTCP program has been planned in a comprehensive manner and due attention has been given to encourage and actively involve all the stakeholders so that global vision to achieve universal access to TB care can be accomplished.
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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 | 0.026 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".