Mental retardation and Xq12–Xq23: candidate loci for nonspecific mental retardation in the male population of the QinBa region
Bibliographic record
Abstract
OBJECTIVES: The higher prevalence of nonspecific mental retardation (NSMR) presents an important socioeconomic and medical issue for families and the whole QinBa region in China. The obvious family aggregation and high heritability indicated that genetic causes play a role in the NSMR population in QinBa. This study discusses the relationship between Xq12-Xq23 region and NSMR in the QinBa area. METHOD: We chose six short tandem repeats--DXS7132, DXS6979, DXS1191, DXS1230, DXS1072, and DXS6804, located in Xq12-Xq23--and analyzed the distribution difference of their alleles between the NSMR and control boys. RESULTS: A significant allele distribution difference was found between NSMR and control boys (all P<0.05) for DXS7132, DXS1191, DXS1230, DXS1072, and DXS6804 but not for DXS6979. CONCLUSION: Our results suggest that Xq12-Xq23 may be the candidate region where there are one or more loci, linked to NSMR in the QinBa region. Further study needs to be carried out for locating the gene responsible for NSMR in this region and a larger sample size and more genetic markers are needed.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".