(Uncontrolled) Donation after Cardiac Determination of Death: A Note of Caution
Bibliographic record
Abstract
“I think there’s a big strong belief in [...] the community … and maybe it’s in the world at large that somehow the doctors are more concerned about harvesting the organs than what’s best for the patient.”1 In the past 45 years, organ and tissue recovery and transplantation have moved from the occasional and experimental to a standard of care for end-stage organ failure; receiving an organ transplant is for many the only opportunity for increased quantity and/or quality of life. The increasing prevalence of diseases such as viral hepatitis, diabetes, and hypertension has significantly increased the incidence of end-organ failure. Additionally, surgical advances have permitted less stringent qualification criteria, so that people of advanced age or patients who may be in a physiologically fragile state are now eligible to be organ recipients. These changes have created a significant demand for organs.
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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 | 0.049 | 0.086 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.007 | 0.004 |
| Research integrity | 0.034 | 0.059 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".