Bibliographic record
Abstract
Tuberous sclerosis complex (TSC) is an autosomal dominant disorder characterised by the \ndevelopment of hamartomas in multiple organs and tissues. TSC is caused by mutations in \neither the TSC1 or TSC2 gene. We searched for mutations in both genes in a cohort of 490 \npatients diagnosed with or suspected of having TSC using a combination of denaturing gradient \ngel electrophoresis, single-strand conformational polymorphism, direct sequencing, fluorescent \nin situ hybridisation and Southern blotting. We identified pathogenic mutations in 362 patients, \na mutation detection rate of 74%. Of these 362 patients, 276 had a definite clinical diagnosis of \nTSC and in these patients 235 mutations were identified, a mutation detection rate of 85%. The \nratio of TSC2:TSC1 mutations was 3.4:1. In our cohort, both TSC1 mutations and mutations in \nfamilial TSC2 cases were associated with phenotypes less severe than de novo TSC2 mutations. \nInterestingly, consistent with other studies, the phenotypes of the patients in which no mutation \nwas identified were, overall, less severe than those of patients with either a known TSC1 or TSC2 \nmutation.
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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 | 0.000 | 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) | 0.002 | 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".