Bibliographic record
Abstract
Like prospectors scouring the reaches of the American frontier, many physicians regularly conduct their own kind of prospecting in the intensive care unit (ICU), seeking to optimize postoperative urine output in their patients after cardiac surgery. The association between renal dysfunction and adverse outcomes has been demonstrated numerous times—in cardiac surgery patients1 and others2—but the decision for and timing of intervention are less clear. In their Expert Review, Merritt-Genore and colleagues3 attempt to provide insight into this important question by examining the evidence for early and late initiation of renal replacement therapy (RRT) for acute renal injury or failure after cardiac surgery.
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 | 0.016 | 0.150 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.008 | 0.005 |
| Research integrity | 0.047 | 0.036 |
| Insufficient payload (model declined to judge) | 0.070 | 0.027 |
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".