Quantification of Forensic DNA from Various Regions of Human Teeth
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
When the use of traditional forensic identification methods such as fingerprints or dental radiographs is difficult or impossible, identification by DNA analysis has proven valuable. In situations such as explosions or airplane crashes, identification is even more difficult because human remains are often fragmented and may be commingled. Teeth are a useful source of DNA and can often survive extreme environmental conditions. However, teeth may be fragmented into several identifiable regions. Therefore it is important to determine if DNA is present in forensically significant yields in all regions of the tooth. The main objectives of this study were to determine which region(s) of the tooth contains quantifiable DNA, if all regions contain similar yields of DNA and whether there is enough DNA in all regions to justify DNA extraction from a found tooth fragment. Results demonstrate that there is sufficient quantity of DNA in the crown body, root body, and root tip to support DNA extraction. Additionally, the root body is the region with the highest yield of DNA. This information will aid forensic DNA analysts in producing a useful DNA profile in a timely and cost-effective manner.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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