Bibliographic record
Abstract
Research in the intensive care unit (ICU) is commonly thought to pose 'serious risk' to study participants. This perception may be at the root of a variety of impediments to the conduct of clinical trials in the ICU setting. Component analysis offers a promising approach to the ethical analysis of ICU research. Because clinical trials commonly involve a mixture of study interventions, therapeutic and nontherapeutic procedures must be analyzed separately. Therapeutic procedures must meet the requirement of clinical equipoise. Risks associated with nontherapeutic procedures must be minimized consistent with sound scientific design, and be deemed reasonable in relation to the knowledge to be gained. When research involves a vulnerable population, such as adults incapable of providing informed consent, nontherapeutic risks are limited to a minor increase over minimal risk. Understood in this way, the incremental risk posed by participation in ICU research may be minimal. This realization has important implications for review by institutional review boards of such research and for the informed consent process.
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 | 0.040 | 0.131 |
| Meta-epidemiology (narrow) | 0.006 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.006 | 0.016 |
| Scholarly communication | 0.015 | 0.010 |
| Open science | 0.008 | 0.003 |
| Research integrity | 0.039 | 0.059 |
| Insufficient payload (model declined to judge) | 0.003 | 0.005 |
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".