International guideline development for the determination of death
Bibliographic record
Abstract
INTRODUCTION AND METHODS: This report summarizes the results of the first phase in the development of international guidelines for death determination, focusing on the biology of death and the dying process, developed by an invitational forum of international content experts and representatives of a number of professional societies. RESULTS AND CONCLUSIONS: Precise terminology was developed in order to improve clarity in death discussion and debate. Critical events in the physiological sequences leading to cessation of neurological and/or circulatory function were constructed. It was agreed that death determination is primarily clinical and recommendations for preconditions, confounding factors, minimum clinical standards and additional testing were made. A single operational definition of human death was developed: 'the permanent loss of capacity for consciousness and all brainstem functions, as a consequence of permanent cessation of circulation or catastrophic brain injury'. In order to complete the project, in the next phase, a broader group of international stakeholders will develop clinical practice guidelines, based on comprehensive reviews and grading of the existing evidence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.059 | 0.115 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.014 | 0.009 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.010 | 0.006 |
| Research integrity | 0.013 | 0.012 |
| Insufficient payload (model declined to judge) | 0.008 | 0.008 |
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".