Bibliographic record
Abstract
Background Mall is a vast country in west Africa with a population of 13.1 million and a surface area of 1 241 000 [km.sup.2]. Poverty is a major problem, with 63.8% of population living below the poverty threshold. (1) Only 47% of population lives less than 5 km from a health centre. (2) In 2002, DOTS was launched in Mall with financial support from the Canadian International Development Agency and technical assistance from the KNCV Tuberculosis Foundation, the World Health Organization and other partners. In 2005, the programme notified 4883 tuberculosis cases (34/100 000 population), far below the WHO estimates of 36 914 cases. (3) The TB case detection rate for sputum smear-positive pulmonary patients in 2005 was 21%. Mali's HIV/AIDS epidemic seems to be less widespread than in eastern and southern Africa, with an estimated 1.8% of the adult population being infected with HIV. (4) DOTS expansion: achievements and challenges Among the achievements of the Global DOTS Expansion Plan mentioned by in the base paper, Mall has benefited from increased external and internal financial resources, international technical assistance and the Global Drug Facility's provision of quality anti-TB drugs. Laboratory diagnosis has been a major challenge in the initial phase of DOTS expansion. With international technical assistance and availability of additional human and financial resources, the microscopy network has been substantially strengthened. In 2005, 3530 new sputum smear-positive patients were notified, which represents a 26% increase over 2001. During the 1990s and in line with heath sector reform, vertical programmes were abolished or scaled down considerably. Mall has experienced what authors refer to as fashions. Implementation of national TB control guidelines, supervision, monitoring and evaluation were hampered by competing priorities. To address these challenges, the health ministry recruited more staff at the central level and identified regional supervisors. Strengthened monitoring and evaluation led to significant improvement of treatment outcome in most regions. The treatment success rate for new sputum smear-positive patients improved from 61% for 2002 cohort to 77% for mid-2005 cohort, while the default rate significantly decreased from 29% in 2002 to 7% in mid-2005. With further decentralization of treatment, improved supervision and patients' education, higher treatment success rates may be achievable. …
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".