Genetic investigation of pervasive developmental disorders in the Quebec population
Bibliographic record
Abstract
Pervasive developmental disorders are a group of neurodevelopmental-neuropsychiatric disorders that are characterized by variable and severe pervasive impairments in several areas of child development, notably social interaction, communication and imagination. They all share clinical features but differ in the severity and age of onset of the impairments. Except for Rett Syndrome (RTT), the etiology of these disorders is unknown, but there is strong evidence that genetic factors contribute to their pathogenesis. While no major genes have been linked to theses disorders linkages, association and chromosomal studies suggest that many loci may be involved. One aim of the present study was to search for genetics variants associated with autism and other related disorders. This study represents the first family-based association study looking at the entire X chromosome using a French-Canadian autistic population, a genetically homogenous group. We found association between autism and markers at two loci. Our results support the existence of a putative gene located on the X chromosome and moreover the founder effect, in the French-Canadian population, may provide greater power to fine map disease genes especially in complex traits. The second aim of the present thesis was to confirm the involvement of the MECP2 gene in our RTT group of patients. While we confirm the presence of mutations in this gene in our cohort of RTT patients we also demonstrated that clinical stringency greatly influences the mutation detection rate for this disorder.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.004 | 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".