A Case of Parentage Testing in Dog by Microsatellite DNA Typing
Bibliographic record
Abstract
Microsatellite DNA형에 의한 개의 친자감정을 실시한 결과 다음과 같은 결론을 얻었다. Labrador Retriever Pup I과 Pup II는 12개 marker 모두에서 멘델의 유전법칙에 따라 친자관계가 성립되었으나 풍산개인 Pup III은 PEZ1 (106bp/118bp), PEZ10 (276bp/300bp), FHC2010 (228bp/232bp) 등 3개 marker에서 유전법칙에 어긋나 친자관계가 성립되지 않았다. We performed this study to determine the parentage verification of putative dogs. A total of 7 samples (4 Labrador Retriever dog and 3 Poongsan dog) were genotyped by using 12 international markers (PEZ1, PEZ5, PEZ8, PEZ10, PEZ11, PEZ12, PEZ17, PEZ20, PEZ21, FHC2010, FHC2054, FHC2079). This methods consisted of multiplexing PCR procedures, and it showed reasonable amplification of all PCR products. Genotyping was performed with an ABI 310 genetic analyzer. Labrador Retriever Pup I and Pup II were included according to principles of Mendelian genetics in all loci, while Poongsan Pup III was excluded with markers PEZ1 (106/118), PEZ10 (276/300), and FHC2010 (228/232). These results suggest that the present DNA typing is so useful for parentage verification of these two breeds.
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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 | 0.011 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".