Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Advances in cardiovascular medicine fueled by innovative clinical trials have dramatically improved the lives of patients worldwide. Commensurate with this progress has been a decline in morbid and mortal events. Accordingly, an increased propensity to collate patient outcomes in clinical trials has emerged that combines death and nonfatal complications into a single composite event. Despite the acknowledged benefits in trial efficiency from such an approach, this method assumes uniform directionality of each component, does not distinguish the relative clinical significance of each, and counts only the first occurrence of any event in the final tally within a conventional time to first event analysis. In this article, we evaluate the criticisms that have been leveled at this approach and provide an overview of recently published phase III cardiovascular trials using primary composite end points. We then explore what to anticipate from the large cohort of as-yet unpublished clinical trials in this arena. Last, we propose a variety of novel approaches that use composite end points and suggest a path forward to enhancing their use in future clinical trials.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.037 | 0.264 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it