Knowledge gaps in the definition and determination of death
Bibliographic record
Abstract
Keywords brain death Á death by circulatory criteria Á death by neurologic criteria Á definition of death Á determination of death Current practices for determining death by neurologic criteria (DNC) and death by circulatory criteria (DCC) are mainly based on guidelines developed by a consensus process relying heavily on foundational historical practices.Death by neurologic criteria was rooted in the Harvard ad hoc criteria 1 with 50 years of progressive evolution to the World Brain Death Project, 2 but suffers from insufficient direct evidence, and therefore, perpetual debate and unresolved controversies.3,4 Death by circulatory criteria has been derived from consensus and expert ''accepted medical practices.''5 While death affects every one of us, the scientific research base for determining death remains in early development, and many questions surrounding the dying process and death in critical care remain unanswered.In this Reflections article, we explore the knowledge gaps related to various aspects of the definition of death and the criteria for determination of death that were identified during the development of the new Canadian Death Determination Guidelines.6 These Guidelines include a brain-based definition of death and recommendations for death determination by circulatory and neurologic criteria.They were developed according to the principles delineated by the Appraisal of Guidelines, Research and Evaluation II instrument for guideline assessment, 7 with broad stakeholder engagement that included patient family members and the public.The
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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 | 0.066 | 0.192 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.009 | 0.016 |
| Open science | 0.008 | 0.007 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 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".