Ventilation in Acute Respiratory Distress Syndrome
Bibliographic record
Abstract
Interdepartmental Division of Critical Care Medicine, University of Toronto; and, University Health Network and Mount Sinai Hospital, Toronto, ON, Canada Division of Pulmonary and Critical Care Medicine, Columbia University College of Physicians and Surgeons, New York, NY Interdepartmental Division of Critical Care Medicine, Department of Medicine University of Toronto; and Keenan Research Center for Biomedical Science, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, ON, Canada * See also p. e451. Dr. Brodie consulted for Maquet Cardiovascular (research consulting including travel expenses to research meetings; all compensation paid to Columbia University). He served as board member for ALung Technologies (Medical Advisory Board; all compensation paid to Columbia University) and received grant support from Maquet Cardiovascular (research support in the form of equipment for a study). Dr. Slutsky consulted for Maquet Critical Care, Baxter/Gambro, and Novalung (paid consultant). Dr. Fan has disclosed that he does not have any potential conflicts of interest.
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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.014 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 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".