Monitoring and oversight in critical care research.
Bibliographic record
Abstract
Institutionally based research ethics review is a form of peer review that has - for better or worse - become the norm throughout the world. The vast majority of research ethics review takes the form of protocol review alone, conducted in advance of the research. Although oversight and monitoring in clinical research have long been recognized as essential features of sound research ethics, they are seldom exercised in ways that fulfill their motivating goals: to ensure that research is conducted as planned; that research participants comprehend the information presented to them in the consent process; and that the potential benefits and risks of study participation remain acceptable. Annual review of continuing research, monitoring informed consent, monitoring adherence to approved protocols and monitoring integrity of research data comprise the main types of monitoring and oversight activity. We believe that our institutionally based systems of research ethics review and responsibility require greater engagement and participation from researchers and research administrators. The appropriate role of critical care researchers and research administrators is to provide leadership to move toward a greater recognition of the importance of monitoring and oversight for ethical and high quality clinical research.
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 | 0.561 | 0.597 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.008 | 0.036 |
| Scholarly communication | 0.018 | 0.015 |
| Open science | 0.005 | 0.014 |
| Research integrity | 0.008 | 0.014 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".