Duty of care to the undiagnosed patient: Ethical imperative, or just a load of Hogwarts?
Bibliographic record
Abstract
With the restoration of You-Know-Who to full corporeal form, the practice of the dark arts may lead to multitudes being charmed, befuddled and confounded. At present, muggle ethics dictate that aid may be rendered in a life-or limb-threatening situation, but the margins are blurred when neither is at stake. Muggle and wizard healers, fearful of being labelled ambulance chasers, may shy away from approaching those who remain blissfully unaware of their illnesses. We describe 4 case studies in which we intervened as muggle healers, to salutary effect. The afflicted were healed or helped, without bringing the weight of the Ministries of Magic or Magical Healing upon us. We advocate a spirit of cooperation between muggle and magical folk, mindful of the strengths that the healing arts from each community have to offer. As long as the intent is beneficent, healers or even the wizard or muggle on the street may intervene and render aid to the afflicted.
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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 | 0.013 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.011 | 0.039 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.015 | 0.020 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".