Exploring healthcare landscape in urban Bangladesh: findings from health facility mapping of Dinajpur municipality in Bangladesh
Bibliographic record
Abstract
This study was funded by Options Consultancy Services Limited, UK, through Urban Health System Strengthening Project (UHSSP). icddr,b acknowledges with gratitude the commitment of Options Consultancy Services Limited, the UK to its research efforts. icddr,b is also grateful to the Governments of Bangladesh, Canada, Sweden, and the UK for providing core/unrestricted support. Special thanks to the Directorate General of Health Services (DGHS), Civil Surgeon and the Mayor of Dinajpur Municipality, and Directorate General of Family Planning (DGFP) for giving permission and supporting the implementation of this study. We also acknowledge all the administrative authorities of health programmes, NGOs, and private health associations for their consent to the survey and for providing information on their delivery points and services. The project could not have been successfully completed without the ceaseless effort of our hard-working teams, a sincere thanks to them.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".