Bibliographic record
Abstract
OBJECTIVES: To review the status of universal newborn screening programs in Canada. METHODS: A brief questionnaire (seven questions) was circulated to one key individual in each province (n=10) and territory (n=3). These individuals were usually physicians or clinical biochemists closely involved in the diagnosis and treatment of genetic metabolic diseases. RESULTS: Universal newborn screening is under provincial jurisdiction. The number of diseases screened for varies and ranges from three to 28. Nine provinces/territories have a central computerized system for tracking initially positive cases. Only five provinces/territories have adequate personnel and resources for follow-up and treatment. Treatment costs are only partially covered in most jurisdictions. Only five provinces/territories have formal advisory committees with official mandates. Expensive, restricted access treatment products for adults with inherited metabolic diseases are only fully available in six provinces/territories. There is very limited access to these products in an additional four provinces/territories. To date, specific informed consent for newborn screening is not required in any province or territory. CONCLUSIONS: Canada is far behind the rest of the developed (and some 'emerging') countries of the world in the field of universal newborn screening. New strategies for advocating expanded screening, follow-up and (long-term) payment of treatment costs on behalf of the potentially affected infants and their families must be devised, and such initiatives should include participation from the new Public Health Agency of Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".