Bibliographic record
Abstract
Abstract Clinical trialists share several similarities with airline pilots. Many of them are investigators (and principal investigators) of large multi‐center randomized controlled trials (RCTs). It is not uncommon for these studies to cost millions of dollars to complete, and they are typically the end stage of a long development process that can easily cost in excess of $100 million dollars. Clinical trialists have often completed advanced training, such as clinical epidemiology, and very definitely have the safety and welfare of trial participants uppermost in their minds. What seems to be missing from the trialist's arsenal is standardization to the process of conducting such studies. More recently, some consensus has developed on how RCTs should be reported, although only a very small percent (2.5%) of the approximately 20,000 health care journals have bought into such reporting standards.
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 | 0.565 | 0.829 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.025 |
| Bibliometrics | 0.027 | 0.032 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.010 | 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".