Bibliographic record
Abstract
Informed consent must be obtained in advance of allpersonal care, investigations, and treatments. For informed consent to be complete and valid, the person giving consent must be capable of making decisions, act voluntarily, and be provided with all necessary information to arrive at a decision that will be in the best interests of the patient. Information sharing has generally focused on available options, risks and benefits of a given intervention, and implications of foregoing the intervention. However, it is difficult to interpret such information without a discussion about the clinical context, natural history of disease, and its associated prognosis.Prognostication, consisting of both the computation (formulation) and disclosure of prognosis, is a key facilitator and enabler for the delivery of truly patient-centered care. Studies have demonstrated that despite patients desiring prognostic information, significant gaps in communication occur between physicians and patients. In a majority of cases of patients with advanced illness there is evidence that disclosure of prognosis has not occurred, thus raising the question as to whether the “informed consent” in this setting is ethically and legally valid.
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 | 0.150 | 0.371 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.009 | 0.014 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.021 | 0.019 |
| Insufficient payload (model declined to judge) | 0.040 | 0.027 |
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".