Manganese, Arsenic, and Infant Mortality in Bangladesh: An Ecological Analysis
Bibliographic record
Abstract
Recent studies in Bangladesh indicate that arsenic and manganese in tube-well water may increase the incidence of infant mortality. The study reported here examined whether these findings could be replicated. Data available from some 600 villages under the care of the nongovernmental organization (NGO) Gonoshasthaya Kendra included details of 29744 live births and 934 infant deaths in a 2-year period, with age and cause. These were analyzed by mean well levels of arsenic and manganese as reported by the British Geological Survey for the 12 upazillas. Odds ratios were calculated by age at death and cause. The effect of arsenic on all-cause infant mortality, although small and not significant, was consistent with earlier reports. The previous finding of an increased risk of infant mortality at concentrations of manganese > or =0.4 mg/L was not evident.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".