Identification of ancient remains through genomic sequencing
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
Studies of ancient DNA have been hindered by the preciousness of remains, the small quantities of undamaged DNA accessible, and the limitations associated with conventional PCR amplification. In these studies, we developed and applied a genomewide adapter-mediated emulsion PCR amplification protocol for ancient mammalian samples estimated to be between 45,000 and 69,000 yr old. Using 454 Life Sciences (Roche) and Illumina sequencing (formerly Solexa sequencing) technologies, we examined over 100 megabases of DNA from amplified extracts, revealing unbiased sequence coverage with substantial amounts of nonredundant nuclear sequences from the sample sources and negligible levels of human contamination. We consistently recorded over 500-fold increases, such that nanogram quantities of starting material could be amplified to microgram quantities. Application of our protocol to a 50,000-yr-old uncharacterized bone sample that was unsuccessful in mitochondrial PCR provided sufficient nuclear sequences for comparison with extant mammals and subsequent phylogenetic classification of the remains. The combined use of emulsion PCR amplification and high-throughput sequencing allows for the generation of large quantities of DNA sequence data from ancient remains. Using such techniques, even small amounts of ancient remains with low levels of endogenous DNA preservation may yield substantial quantities of nuclear DNA, enabling novel applications of ancient DNA genomics to the investigation of extinct phyla.
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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 | 0.001 |
| 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