One Founder/One Gene Hypothesis in a New Expanding Population: Saguenay (Quebec, Canada)
Bibliographic record
Abstract
High frequencies of some rare inherited recessive disorders can be found in the Saguenay region of Quebec, Canada. Four disorders have a carrier frequency of about 0.04 (in the range 0.035-0.05): pseudo-vitamin D-dependent rickets, hereditary tyrosinemia type 1, Charlevoix-Saguenay spastic ataxia, and sensorimotor polyneuropathy with or without agenesis of the corpus callosum. Molecular data suggest that only 1 mutation has been introduced into the population since its founding in the 17th century. The carrier frequencies are much higher than one would expect under a theoretical model that includes variance in family size and population growth (Thompson and Neel 1978). I present a methodology called allele dropping to test the hypothesis that only 1 founder introduced a given mutation. This study is based on 891 ascending genealogies and enables one to measure the extent of allele frequency changes resulting from the demographic history of the population. Two scenarios are tested: neutral and lethal alleles. Lethality has a minor effect because the alleles never reach a frequency high enough for selection to be strong. Twenty-five founders have a probability greater than 1% that a lethal mutation they introduced into the population will reach a carrier frequency between 0.035 and 0.05 in the contemporary population. Moreover, 2 founders have a probability greater than 20% that a lethal allele they introduced into the population will reach this target frequency. Therefore the simplest hypothesis that 1 founder introduced 1 disorder into the population is consistent.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 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".