Intra-Familial Tests of Association between Familial Idiopathic Scoliosis and Linked Regions on 9q31.3–q34.3 and 16p12.3–q22.2
Bibliographic record
Abstract
OBJECTIVE: Custom genotyping of markers in families with familial idiopathic scoliosis were used to fine-map candidate regions on chromosomes 9 and 16 in order to identify candidate genes that contribute to this disorder and prioritize them for next-generation sequence analysis. METHODS: Candidate regions on 9q and 16p-16q, previously identified as linked to familial idiopathic scoliosis in a study of 202 families, were genotyped with a high-density map of single nucleotide polymorphisms. Tests of linkage for fine-mapping and intra-familial tests of association, including tiled regression, were performed on scoliosis as both a qualitative and quantitative trait. RESULTS AND CONCLUSIONS: Nominally significant linkage results were found for markers in both candidate regions. Results from intra-familial tests of association and tiled regression corroborated the linkage findings and identified possible candidate genes suitable for follow-up with next-generation sequencing in these same families. Candidate genes that met our prioritization criteria included FAM129B and CERCAM on chromosome 9 and SYT1, GNAO1, and CDH3 on chromosome 16.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".