Informed Consent: Physician Inexperience is a Material Risk for Patients
Bibliographic record
Abstract
This paper examines the case for an expanded interpretation of the concept of "material risk" such that it necessitates voluntary disclosure of physician inexperience with a specific medical procedure. Informed consent law in the United States, Canada, and most commonwealth jurisdictions has become a driver of standards of risk disclosure by physicians during the informed consent process. The legal standard of risk disclosure expected of a physician hinges on the interpretation of the entity called "material risk." Any impairment of the physician related to drug usage, disease, or alcohol which compounds the risk of a procedure is very likely to be considered material by a patient. This paper argues that physician inexperience is a factor that a reasonable patient would attach significance to and that it should therefore be viewed as a "material risk" requiring disclosure.
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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 | 0.047 | 0.125 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.029 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.014 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 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".