Bibliographic record
Abstract
Modern law approaches patients' consent to treatment not only through liability for unauthorized touching, namely criminal assault and/or civil (non-criminal) battery, but also through liability for negligence. Physicians must exercise appropriate skill in conducting procedures, and in providing patients with information material to the choices that patients have to make. The doctrine of informed consent serves the ethical goal of respecting patients' rights of self-determination. Information is initially pitched at the reasonable, prudent person in the patient's circumstances, and then fine-tuned to what is actually known about the particular patient's needs for information. Elements to be disclosed include the patient's prognosis if untreated, alternative treatment goals and options, the success rate of each option, and its known effects and material risks. Risks include medical risks, but also risks to general well-being such as economic and similar reasonable interests. Consent is a continuing process, not an event or signed form.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.099 | 0.123 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.073 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.018 | 0.019 |
| Insufficient payload (model declined to judge) | 0.007 | 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".