A PCR Multiplex and Database for Forensic DNA Identification of Dogs
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Animal-derived trace evidence is a common finding at crime scenes and may provide an important link between victim(s) and suspect(s). A database of 558 dogs of pure and mixed breeds is described and analyzed with two PCR multiplexes of 17 microsatellites. Summary statistics (number of alleles, expected and observed heterozygosity and power of exclusion) are compared between breeds. Marked population substructure in dog breeds indicates significant inbreeding, and the use of a conservative theta value is recommended in likelihood calculations for determining the significance of a DNA match. Evidence is presented that the informativeness of the canine microsatellites, despite inbreeding, is comparable to the human CODIS loci. Two cases utilizing canine DNA typing, State of Washington v. Kenneth Leuluaialii and George Tuilefano and Crown v. Daniel McGowan, illustrate the potential of canine microsatellite markers for forensic investigations.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it