Bibliographic record
Abstract
We appreciate the comments from Dr. Wildhaber. Biliary atresia (BA) is the most common cause of liver death in children. Through the stool color card screening program, the prognosis of BA can be improved remarkably by early detection and timely surgery. The stool color card screening program is indeed a noninvasive, low-cost, and simple screening tool that is suitable for mass screening.1, 2 We are pleased to learn of the launch of the Swiss national biliary atresia screening program. This is a positive support to our stool card screening program in Taiwan. We hope to see more countries begin the implementation of the universal stool color card screening program for BA in children. As we understand, experts from quite a number of countries, including Canada, Malaysia, Australia, and the Philippines, among others, have started or are planning a pilot study for the stool color card screening program for BA. Our stool color card is available in other languages for new immigrants to Taiwan, including versions in English, Vietnamese, Thai, Indonesian, and Khmer (Kampuchea). In addition, the stool color card has been integrated into a child health booklet. Educational lectures were given to health and medical personnel, and periodically to day care workers.. Posters were also put up in local clinics and hospitals to propagate the related knowledge. Many previous studies had shown the importance of earlier detection for BA.3-5 Our experience provides evidence that the stool color card is a good screening tool for BA. Continuous efforts to actively promote early detection is mandatory to improve the long-term outcome of BA. We believe that the stool color card is a blessing for children's health. Tien-Hau Lien M.D.*, Mei-Hwei Chang M.D.*, * Department of Pediatrics, National Taiwan University Hospital, Taipei, Taiwan.
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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 | 0.006 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.027 | 0.036 |
| Insufficient payload (model declined to judge) | 0.039 | 0.030 |
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".