Case 11 : United Hearts: Fostering Interdisciplinary Collaboration for the Detection of Critical Heart Defects in Newborns
Bibliographic record
Abstract
Newborn Screening Ontario (NSO) prepares to implement screening for critical congenital heart defects (CCHDs) in all newborns born in Ontario. Janet Marcadier, a genetic counsellor at NSO, recognizes the particular challenges of implementing a point-of-care newborn screening test that will be performed by submitters (nurses, midwives) across the province. The other 29 conditions screened for by NSO do not involve a point-of-care test but rather testing is done in the NSO laboratory. While standardization for a provincial program is important, there are many contextual factors that will impact CCHD screening implementation at each specific birth site. Interdisciplinary collaboration among health care providers will be essential in implementation. How could NSO foster interdisciplinary collaboration through implementation planning? NSO needs to consider how primary care teams are often dynamic and include different health care providers depending on the needs of the patient. Would interdisciplinary collaboration help to ensure screening compliance among submitters? By applying concepts of implementation research, context-specific protocols can be developed for interdisciplinary teams at different birth sites in Ontario.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".