Newborn screening for cystic fibrosis in Alberta: Two years of experience
Bibliographic record
Abstract
On April 1, 2007, Alberta became the first province in Canada to introduce cystic fibrosis (CF) to its newborn screening program. The Alberta protocol involves a two-tier algorithm involving an immunoreactive trypsinogen measurement followed by molecular analysis using a CF panel for 39 mutations. Positive screens are followed up with sweat chloride testing and an assessment by a CF specialist. Of the 99,408 newborns screened in Alberta during the first two years of the program, 221 had a positive CF newborn screen. The program subsequently identified and initiated treatment in 31 newborns with CF. A relatively high frequency of the R117H mutation and the M1101K mutation was noted. The M1101K mutation is common in the Hutterite population. The presence of the R117H mutation has created both counselling and management dilemmas. The ability to offer CF transmembrane regulator full sequencing may help resolve diagnostic dilemmas. Counselling and management challenges are created when mutations are mild or of unknown clinical significance.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.002 |
| 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".