Bibliographic record
Abstract
Background: Physician-assisted suicide (PAS) laws have been enacted in five US States and, along with physician-administered euthanasia, in Canada and the Netherlands. Sources of data: Annual reports of the Oregon Health Authority and published research papers. Areas of agreement: Not all recipients of lethal drugs use them to end their lives. Improvements in palliative care provision. Areas of controversy: Rising numbers of deaths from PAS. Emergence of 'doctor shopping' and multiple-prescribing. Absence of qualitative scrutiny of assessment process. No re-assessment or oversight when prescribed drugs are ingested. Recent pressures to extend Oregon's PAS law. Growing points: Reasons given for seeking PAS indicate this is a societal rather than a clinical issue and raise the question whether adjudicating on requests for legalized PAS is an appropriate role for doctors. Areas for timely research: Research into quality of decision-making in requests for PAS and into potential role of doctors as expert witnesses rather than judges in requests for PAS.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".