Bibliographic record
Abstract
The current main source of transplantable organs is from heart-beating donors. These are patients who have suffered a catastrophic brain injury, been ventilated, declared dead by neurological criteria, and had their vital functions maintained mechanically until the point of transplantation. But the demand for organs far outstrips the supply, and these patients are not the only potential donors. The idea behind non-heart-beating transplantation is to expand the donor pool by including in it patients who are in hopeless conditions but who are not dying because of brain injury and hence will not suffer the neurological death necessary to become heart-beating donors. As long as we continue to hold the so-called dead donor rule, according to which dying donors cannot have their organs taken before they are dead, this requires that death be able to be declared by alternative criteria, specifically by cardiopulmonary criteria. The challenge is to find such criteria that will identify a state that the public will readily recognize as death and that will facilitate non-heart-beating transplantation.I am grateful to Don Brown for encouragement, advice, and stimulating discussion and to Michael Feld for reminding me just how resilient a theory utilitarianism is.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".