Beyond Mortality: Future Clinical Research in Acute Lung Injury
Bibliographic record
Abstract
Mortality in National Heart, Lung and Blood Institute-sponsored clinical trials of treatments for acute lung injury (ALI) has decreased dramatically during the past two decades. As a consequence, design of such trials based on a mortality outcome requires ever-increasing numbers of patients. Recognizing that advances in clinical trial design might be applicable to these trials and might allow trials with fewer patients, the National Heart, Lung and Blood Institute convened a workshop of extramural experts from several disciplines. The workshop assessed the current state of clinical research addressing ALI, identified research needs, and recommended: (1) continued performance of trials evaluating treatments of patients with ALI; (2) development of strategies to perform ALI prevention trials; (3) observational studies of patients without ALI undergoing prolonged mechanical ventilation; and (4) development of a standardized format for reporting methods, endpoints, and results of ALI trials.
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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 | 0.197 | 0.194 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.003 | 0.014 |
| Scholarly communication | 0.011 | 0.026 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.014 | 0.016 |
| Insufficient payload (model declined to judge) | 0.011 | 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; 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".