A Consensus Approach to the Classification of Pediatric Pulmonary Hypertensive Vascular Disease: Report from the PVRI Pediatric Taskforce, Panama 2011
Bibliographic record
Abstract
Current classifications of pulmonary hypertension have contributed a great deal to our understanding of pulmonary vascular disease, facilitated drug trials, and improved our understanding of congenital heart disease in adult survivors. However, these classifications are not applicable readily to pediatric disease. The classification system that we propose is based firmly in clinical practice. The specific aims of this new system are to improve diagnostic strategies, to promote appropriate clinical investigation, to improve our understanding of disease pathogenesis, physiology and epidemiology, and to guide the development of human disease models in laboratory and animal studies. It should be also an educational resource. We emphasize the concepts of perinatal maladaptation, maldevelopment and pulmonary hypoplasia as causative factors in pediatric pulmonary hypertension. We highlight the importance of genetic, chromosomal and multiple congenital malformation syndromes in the presentation of pediatric pulmonary hypertension. We divide pediatric pulmonary hypertensive vascular disease into 10 broad categories.
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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 | 0.032 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| 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".