Newborn urine screening programme in the province of Quebec: An update of 30 years' experience
Bibliographic record
Abstract
The introduction of our voluntary mass screening programme in 1971, in the province of Quebec, has permitted us to detect different inborn errors of metabolism in the newborn population using a thin-layer chromatographic (TLC) technique with sequential use of different sprays on the same plate. Abnormalities in amino acids and organic acids are detected in urine filter paper specimens of 21-day-old babies. Initial parental compliance is 90% and climbs to 99.25% for repeat sample requests. Screening is centralized in one laboratory, while diagnosis, counselling, management and follow-up are done in four regional centres. Over 25 inherited Mendelian disorders can be identified. There have been certain modifications in our programme throughout the years in order to increase efficiency, screen for a larger number of disorders, improve the quality of the collection of the urine filter paper samples, increase parental compliance and better manage the data bank. However, one goal has remained a priority: early prevention of genetic diseases. We present an overall view of our screening programme with an add-on technique to detect different organic acidurias, our recent statistics and the modifications implemented over the years.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".