Methodology of the Pediatric Acute Lung Injury Consensus Conference
Bibliographic record
Abstract
OBJECTIVE: This article describes the methodology used for the Pediatric Acute Lung Injury Consensus Conference. DESIGN: Consensus conference of international experts in pediatric acute respiratory distress syndrome using the Research ANd Development/University of California, Los Angeles appropriateness method and an expert recommendations process developed by the French-speaking intensive care society. Topics related to pediatric acute respiratory distress syndrome were divided into nine subgroups with a review of the literature. SETTING: A group of 27 experts met three times over the course of 2 years and collaborated in their respective subgroups to define pediatric acute respiratory distress syndrome and to make recommendations regarding treatment and future research priorities. MAIN RESULTS: The consensus conference resulted in summary of recommendations published in Pediatric Critical Care Medicine, the present Pediatric Acute Lung Injury Consensus Conference methodology article, articles on the nine pediatric acute respiratory distress syndrome subtopics, and a review of pediatric acute respiratory distress syndrome pathophysiology published in this supplement of Pediatric Critical Care Medicine. CONCLUSIONS: The methodology described involved experts from around the world and the use of modern information technology. This resulted in recommendations for pediatric acute respiratory distress syndrome management, the identification of current research gaps, and future priorities.
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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 | 0.275 | 0.335 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.013 | 0.008 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".