Advances in molecular cytogenetics for the evaluation of mental retardation
Bibliographic record
Abstract
Recent years have witnessed rapid advances in molecular cytogenetics and its impact in studying mental retardation (MR). We review new molecular cytogenetic methods, including interphase fluorescence in situ hyrbridization (FISH), comparative genomic hybridization (CGH), multicolor karyotyping, telomere FISH, primed in situ labeling (PRINS), genotyping, microdissection, and microarray for the evaluation of MR. These new methods are very useful in two major aspects: further characterization of chromosome abnormalities as detected with routine banding analysis, including additions, duplications, deletions, translocations, markers, or complex aberrations; and screening for "hidden" chromosome aberrations in patients with an apparently normal karyotype. These new methods have great diagnostic potential in prenatal, postnatal, and preimplantational settings. Although powerful, at this point, they are primarily research tools in nature. It is essential that these new methods be used in conjunction with standard methods in order to maximize obtainable information for better management of patients with MR.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.006 |
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".