Learning from each other: The hidden benefit of practice variation
Bibliographic record
Abstract
It has long been recognized that there is significant variation in the way that centers approach clinical management and problems within pediatric transplantation. This has recently been highlighted in two publications by the PHTS showing practice variation in both surveillance for cardiac allograft vasculopathy and diagnosis of acute rejection. These differences in practice are important to recognize and serve as the foundation for collaborative learning, developing research questions, and implementing quality improvement initiatives. To further understand the practice variation within the society, and to begin the process of learning from each other, the society has developed a Clinical Approach Working Group, whose task is to tackle issues seen in transplant and integrate current literature with clinical protocols and experience from the individual sites. The early work of this group has results in the series of Clinical approach articles presented in this issue of Pediatric Transplantation.
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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 | 0.034 | 0.142 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.015 | 0.012 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.015 | 0.026 |
| Insufficient payload (model declined to judge) | 0.006 | 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; 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".