Reliability and Reproducibility of Classification of Children as “Bleeders” Versus “Non-Bleeders” Using a Questionnaire for Significant Mucocutaneous Bleeding
Bibliographic record
Abstract
The diagnosis of type 1 von Willebrand disease (VWD), the most common inherited bleeding disorder in humans, is greatly dependent on an accurate diagnosis of significant mucocutaneous bleeding. In a previous study, the authors modified the criteria of the International Society on Thrombosis and Haemostasis for significant mucocutaneous bleeding to a format, the Hospital for Sick Children (HSC) criteria, that was more applicable to diagnose significant mucocutaneous bleeding in children. To assess the reliability and reproducibility of classification of subjects as "bleeders" versus "non-bleeders" using a questionnaire for significant mucocutaneous bleeding targeted to children, 39 subjects interviewed for a previous HSC VWD study were reinterviewed for the current study. The original bleeding classification was confirmed in 80% of subjects interviewed for a second time, indicating that this method of classification is reproducible (kappa = 0.65), with a "substantial" agreement among the investigators who reviewed the questionnaire responses (kappa = 0.71). The validity and utility of the HSC questionnaire for primary screening of children with suspected mucocutaneous bleeding disorders merits assessment in further clinical studies.
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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 | 0.031 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".