Organ donation after medical assistance in dying: a scoping review protocol
Bibliographic record
Abstract
ABSTRACT Objective: This scoping review will collate and summarize the current literature on what is known worldwide about organ donation following medical assistance in dying. The information gathered will be used to inform updates of current and future policies on organ donation following medical assistance in dying in Canada. Introduction: Medical assistance in dying is a controversial and contentious issue worldwide. While more countries are legalizing medical assistance in this regard, very few allow organ donation after such assistance has been given. At present, Canada, Belgium, and The Netherlands are the only three countries that permit this procedure. This scoping review will be conducted to summarize the current state of evidence and practices regarding organ donation following medical assistance in dying. Inclusion criteria: This review will consider articles and documents on individuals who choose organ donation following medical assistance in dying. Articles will be considered for inclusion if they explore organ donation following medical assistance in dying at home or in any health care setting in any country. Quantitative and qualitative studies, text and opinion papers, gray literature, and unpublished materials provided by researchers will be considered for inclusion. Methods: This review will be conducted in accordance with the JBI methodology for scoping reviews. Published and unpublished materials will be included. Databases will include MEDLINE, Embase, CINAHL, PsycINFO, Web of Science – Science Citation Index and Social Science Citation Index, and Academic Search Complete. Relevant gray literature and materials from organ donation organizations will be included. Two independent reviewers will screen all material, extract data, and complete the descriptive examination.
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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 | 0.136 | 0.097 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.013 | 0.010 |
| Bibliometrics | 0.018 | 0.014 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.010 | 0.008 |
| Insufficient payload (model declined to judge) | 0.077 | 0.019 |
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".