Homozygosity mapping of a third Joubert syndrome locus to 6q23
Bibliographic record
Abstract
BACKGROUND: Joubert syndrome (JS) is a recessively inherited disorder characterised by hypotonia at birth and developmental delay, followed by truncal ataxia and cognitive impairment, characteristic neuroimaging findings (cerebellar vermis hypoplasia, "molar tooth sign") and suggestive facial features. JS is clinically heterogeneous with some patients presenting with breathing abnormalities in the neonatal period, oculomotor apraxia, retinal dystrophy, retinal coloboma, ptosis, hexadactyly, and nephronophtisis or cystic dysplastic kidneys. JS is also genetically heterogeneous, with two known loci, on 9q34 (JBTS1) and 11p11-q12 (CORS2), representing only a fraction of cases. METHODS: A large consanguineous Joubert family (five affected) was analysed for linkage with a marker set covering the entire genome and 16 smaller families were subsequently tested for candidate loci. RESULTS: We report here the identification of a third locus in 6q23 (JBTS3) from the study of two consanguineous families. LOD score calculation, including the consanguinity loops, gave a maximum value of 4.1 and 2.3 at q = 0 for the two families, respectively. CONCLUSIONS: Linkage between the disease and the D6S1620-D6S1699 haplotype spanning a 13.1 cM interval is demonstrated. Genotype-phenotype studies indicate that, unlike CORS2, JBTS3 appears not to be associated with renal dysfunction.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".