Contribution de la commission d’éthique de la Société de réanimation de langue française à un scénario de mise en oeuvre des prélèvements d’organes de type Maastricht III en France
Bibliographic record
Abstract
French regulation allows organ donation after cardiac death. Type III-Maastrich classification refers to cardiac arrest occurring after the withdrawal of life-sustaining treatments. The possibility of organ donation in such circumstances is currently discussed by the French authorities. This article describes the ethical scenario that should be considered as the frame for this procedure. Akey-point is the respect of the dying person, requiring no change in the patient’s and proxies’ care while aiming possible organ donation. The dead donor rule implies that organ donation should not cause or hasten death. Amajor ethical issue is the transition between the discussion with proxies about withdrawal of life-sustaining treatments and the announcement of the possibility of organ donation after death. This point should be better addressed by a combined interview of proxies with the medical team caring for the patient and the transplant coordinators. Implementation of non-heart-beating donation is discussed in this article, including the location where life-sustaining treatments should be withdrawn (intensive care unit versus operating theatre).
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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 | 0.025 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.015 | 0.013 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".