High-resolution Human Genome Scanning Using Whole-genome BAC Arrays
Bibliographic record
Abstract
Constitutional chromosome abnormalities are a frequent cause of many human syndromes, such as infertility, congenital anomalies, and mental retardation (Gardner and Sutherland 1996). Cytogenetic analysis ofchromosomal integrity in patients with mental retardation (MR) indicates that 40% of severe (IQ<55) and10–20% of mild (IQ = 55–70) MR is caused by chromosomal anomalies (Flint et al. 1995). However, due to thepoor resolution of conventional cytogenetic analysis,subtle chromosomal rearrangements (<3 Mb) may bemissed in a significant proportion of mild MR cases. Recent studies focusing on the subtelomeric regions of patients with idiopathic MR indeed indicated that theprevalence of subtle subtelomeric rearrangements couldbe as high as 6% in these patients (Flint et al. 1995;Knight et al. 1999), and it is now widely accepted thatsubmicroscopic telomeric rearrangements are a significant cause of MR. It is quite natural to hypothesize thata substantial proportion of idiopathic MR may be causedby subtle rearrangements in other parts of the genomethat were never detected due to a low resolution of cytogenetic analysis and the unavailability of high-resolution genome-scanning techniques. The fact that chromosomal rearrangements can occur in almost any region ofthe genome (Brewer et al. 1998, 1999), and the existenceof subtle microdeletions and microduplications alongthe chromosomal arms in over 10 clinical syndromes associated with MR (Shapira 1998), support this hypothesis...
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".