The National Association of Medical Examiners Position Paper on the Investigation and Certification of Pediatric Deaths From Environmental Neglect
Bibliographic record
Abstract
ABSTRACT: Pediatric deaths that occur because of environmental neglect often involve 4 common scenarios: (1) hyperthermia due to environmental exposure, (2) ingestion of an accessible drug or poison, (3) unwitnessed/unsupervised drownings, and (4) unsafe sleep practices. Given the same fact pattern, the manner of death will vary from accident to homicide to undetermined based on local custom and/or the certifier's training and experience. Medical examiner/coroner death certifications are administrative public health determinations made for vital statistical purposes. Because the manner of death is an opinion, it is understandable that manner determinations may vary among practitioners. No prosecutor, judge, or jury is bound by the opinions expressed on the death certificate. This position paper does not dictate how these deaths should be certified. Rather, it describes the challenges of the investigations and manner determinations in these deaths. It provides specific criteria that may improve consistency of certification. Because pediatric deaths often are of public interest, this paper provides the medical examiner/coroner with a professional overview of such manner determination issues to assist various stakeholders in understanding these challenges and variations.
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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 | 0.032 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.012 | 0.009 |
| Insufficient payload (model declined to judge) | 0.012 | 0.007 |
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".