Prevalence of weak D phenotypes in the general population of Québec, Canada: A focus on weak D type 42
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Weak D type 42 accounts for an unusually high proportion of weak D phenotypes in Québec (Canada), which contrasts with other predominantly White populations. However, its prevalence in the general population is unknown. We estimated the prevalence of weak D type 42 and other common weak D phenotypes in Québec. MATERIALS AND METHODS: We screened for RHD*01W.42 alleles among 1000 individuals of CARTaGENE-a cohort representative of Québec's population. The prevalence of weak D type 42 was calculated based on the allele frequency of RHD*01W.42 and d (i.e., all recessive alleles that confer a D- phenotype), assuming a Hardy-Weinberg equilibrium. This prevalence was then leveraged to calculate that of other common weak D phenotypes, using published prevalence estimates among weak D phenotypes. RESULTS: Two individuals harboured the RHD*01W.42/RHD*01 heterozygous genotype. Assuming an allele frequency of 38.19% for d, the overall prevalence of weak D type 42 was 0.08%. The following prevalence estimates were also obtained: 0.44% for all weak D phenotypes and 0.07%, 0.01% and 0.04% for weak D types 1, 2 and 3, respectively. CONCLUSION: Québec has the highest documented prevalence of weak D type 42, which was estimated at 0.08%.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".