The World Database for Pediatric and Congenital Heart Surgery: The Dawn of a New Era of Global Communication and Quality Improvement in Congenital Heart Disease
Bibliographic record
Abstract
The World Society for Pediatric and Congenital Heart Surgery was founded with the mission to "promote the highest quality comprehensive cardiac care to all patients with congenital heart disease, from the fetus to the adult, regardless of the patient's economic means, with an emphasis on excellence in teaching, research, and community service." Early on, the Society's members realized that a crucial step in meeting this goal was to establish a global database that would collect vital information, allowing cardiac surgical centers worldwide to benchmark their outcomes and improve the quality of congenital heart disease care. With tireless efforts from all corners of the globe and utilizing the vast experience and invaluable input of multiple international experts, such a platform of global information exchange was created: The World Database for Pediatric and Congenital Heart Disease went live on January 1, 2017. This database has been thoughtfully designed to produce meaningful performance and quality analyses of surgical outcomes extending beyond immediate hospital survival, allowing capture of important morbidities and mortalities for up to 1 year postoperatively. In order to advance the societal mission, this quality improvement program is available free of charge to WSPCHS members. In establishing the World Database, the Society has taken an essential step to further the process of global improvement in care for children with congenital heart disease.
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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 | 0.010 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.009 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".