The 2012 Interlaboratory Comparison of Forensic DNA Typing in Thailand
Bibliographic record
Abstract
Objective: To evaluate the results of the 2012 interlaboratory comparison for forensic deoxyribonucleic acid (DNA) typing including autosomal short tandem repeat loci (aSTR), Y-chromosome short tandem repeat loci (Y-STR), X-chromosome short tandem repeat loci (X-STR) and mitochondrial DNA (mtDNA). Material and Methods: The analysis was performed using 4 blood samples stored on FTA® cards. Twelve laboratories in Thailand participated in this study. The results from each participant were compared with the consensus results. Results: The analysis of aSTR, Y-STR, X-STR and mtDNA were performed in 12 (100.0%), 8 (66.7%), 6 (50.0%) and 7 (58.3%) laboratories, respectively. All DNA profiles of aSTR, Y-STR and X-STR from all the participating laboratories showed the same STR profiles. However, the calculation of forensic DNA typing statistical values and the format of laboratory reports among these laboratories showed several variations. Only the mtDNA test showed some variations among the laboratories. Conclusion: For aSTR, Y-STR and X-STR tests, the trainings in statistical calculation of forensic DNA typing are required. For mtDNA test, workshop training should be established. Furthermore, a standard guideline for forensic DNA typing reports should be released in order to provide all the necessary information in the laboratory reports.
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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 | 0.039 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".