P.009 Physician assisted death and the neurosurgeon
Bibliographic record
Abstract
Background: The Supreme Court of Canada (SCC) recently rendered a decision striking down the Criminal Code absolute prohibition on providing assisted dying. End of life decisions are commonly encountered by neurosurgeons due to the nature of their practice. Neurosurgeons will be faced with patients requesting PAD in the near future. Methods: The recent SCC ruling heralds a change that will radically alter a most basic tenet that has historically guided physicians and surgeons. A subcommittee of the Canadian Neurosurgical Society (CNSS) was formed to generate a position statement to reflect the interests of both neurosurgeons and their patients. Results: Fundamental issues regarding the implementation of PAD identified include: Clarity of legislation The creation of an independent, third party referral service Effective safeguards and oversight of the entire process -The right to “conscientious objection” on the part of hysicians who do not wish to be involved in PAD Conclusions: The CNSS urges clarity in legislation regarding PAD and strict oversight in its implementation to reduce potential harm. We also support the creation of an independent, third party referral service which would serve to respect the conscience of those health care providers who do not wish to actively participate in PAD.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.011 | 0.009 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.011 | 0.009 |
| Insufficient payload (model declined to judge) | 0.020 | 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".