Bibliographic record
Abstract
BACKGROUND: Individuals suffering from severe disorders of consciousness (DOC) face a bleak prognosis and are susceptible to therapeutic neglect according to Fins. Because of the increasing occurrence of severe brain injury, some physicians and researchers take the study of DOC to be a moral imperative and perceive novel technologies, such as Deep Brain Stimulation (DBS), as offering potential therapeutic benefit. METHOD: This article examines the decisional process faced by proxy decision-makers for patients with severe DOC when confronted by novel treatments such as DBS. RESULTS: If there is awareness in the literature that surrogate consent is complicated by the contingencies of severe brain injury such as disability and the possibility of long-term care, surrogate consent is often equated with substituted judgement and taking the best interests of the patient into account. However, for surrogates of patients with severe DOC, advocacy becomes a central component of the surrogate's role as there is no established standard of care for these patients in the post-acute phase. If participation in research is offered, the surrogate may perceive research participation as a way of providing benefits such as stimulation and some rehabilitation services for the patient. CONCLUSION: Researchers need to be aware how the absence of a standard of care can shape surrogate choice.
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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 | 0.162 | 0.317 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.063 |
| Scholarly communication | 0.017 | 0.022 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.023 | 0.016 |
| 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".