The Canadian Pediatric Surgery Network Congenital Diaphragmatic Hernia Evidence Review Project: Developing national guidelines for care
Bibliographic record
Abstract
The Canadian Pediatric Surgery Network (CAPSNet) has been collecting population-based data regarding congenital diaphragmatic hernia (CDH) across its 17 perinatal sites since 2005. With >500 infants registered to date, CAPSNet has addressed many critical knowledge gaps pertaining to CDH care. Most importantly, it has identified variability in both CDH practice and outcome across Canada. Using the successful Evidence-based Practice for Improving Quality (EPIQ) method, CAPSNet is undertaking a national, multidisciplinary effort to standardize best practices for CDH, from prenatal diagnosis to hospital discharge, based on the best available evidence. The present article outlines the value of clinical research networks and the process CAPSNet will undertake to produce national consensus guidelines for CDH care.
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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 | 0.085 | 0.195 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.026 | 0.023 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.010 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".