Allele Frequencies of Four Short Tandem Repeat Loci in Chinese Han Population
Bibliographic record
Abstract
Abstract Genomic DNA was obtained from peripheral blood extracted with Chelex-100 method (1). PCR was performed in a total reaction volume of 20 µL containing 20 ng genomic DNA, 0.2 µM each primer, 10 mM Tris-HCl buffer (pH 8.3), 50 mM KCl, 1.5 mM MgCl2, 200 RM each dNTP, and 1 U Taq DNA polymerase (BioStar, Canada). Primer sequences: D2S1788: 5 -aat gga tgg aca aat gga tg-3, 5 -ccc tcc ata att aga tga gcc-3; D6S1043: 5 -caa gga tgg gtg gat caa ta-3, 5 -ttg tat gag cca ctt ccc at-3; D7S3048: 5 -ctg gag ctg cat agt gtc ct-3, 5 -aat cat ccc tgt gtg ctt tc-3; D12S1064: 5 -act act cca agg ttc cag cc-3, 5 -aat att gac ttt ctc ttg cta ccc-3. PCR conditions: 95°C for 2 min soak, 32 cycles of 35 s at 94°C, 35 s at 60°C, 40 s at 72°C followed by a 5 min extension period at 72°C. The amplification products were separated in a vertical, native polyacrylamide gel (6% T; 5% C) and visualized by silver staining. Allele frequencies and others statistics parameters for forensic and paternity were determined for each locus by the PowerStats software packages (2). The Hardy-Weinberg equilibrium test (HWE) was performed by an exact test (3). None of the analyzed loci showed deviations from HWE (P > 0.05) in the population studied. The complete dataset is available to any interested researcher upon request to the authors.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".