Randomized controlled trials in resuscitation
Bibliographic record
Abstract
Randomized controlled trials (RCTs) are a gold standard in research and crucial to our understanding of resuscitation science. Many trials in resuscitation have had neutral findings, questioning which treatments are effective in cardiac resuscitation. While it is possible than many interventions do not improve patient outcomes, it is also possible that the large proportion of neutral findings are partially due to design limitations. RCTs can be challenging to implement, and require extensive resources, time, and funding. In addition, conducting RCTs in the out-of-hospital setting provides unique challenges that must be considered for a successful trial. This article will outline many important aspects of conducting trials in resuscitation in the out-of-hospital setting including patient and outcome selection, trial design, and statistical analysis.
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 | 0.321 | 0.658 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.008 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.018 | 0.018 |
| Insufficient payload (model declined to judge) | 0.041 | 0.009 |
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".