Characterization of the D18S535 STR Locus in Northern Ontario European and Aboriginal Populations for Forensic Purposes
Bibliographic record
Abstract
Genetic characterization of one European and three aboriginal populations from northern Ontario was undertaken to assess the utility of the D18S535 short tandem repeat locus (STR) as a genetic marker for forensic DNA typing in the region. The D18S535 locus was amplified using monoplex polymerase chain reaction (PCR), separated by denaturing polyacrylamide gel electrophoresis (PAGE), and visualized using the silver-stain detection method. The generated population data demonstrated that the D18S535 locus is highly polymorphic with a heterozygosity of > or = 0.75. The exact test showed violations of Hardy-Weinberg equilibrium in two of the aboriginal populations. Pairwise comparisons of allele-frequency distributions indicated that the four northern Ontario populations were significantly different from each other. This test also revealed that the northern Ontario populations differed significantly from ten European populations (from Germany, Spain, and Croatia) and one population from South America (from Argentina). Forensic parameters showed that the D18S535 locus is highly discriminating (power of discrimination > or = 0.85, chance of exclusion > or = 0.51); however, the lack of Hardy-Weinberg equilibrium in some of the populations must be taken into account in the application of these results to northern Ontario forensic casework.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.001 | 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".