Distinguishing Forest and Savanna African Elephants Using Short Nuclear DNA Sequences
Why this work is in the frame
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Bibliographic record
Abstract
A more complete description of African elephant phylogeography would require a method that distinguishes forest and savanna elephants using DNA from low-quality samples. Although mitochondrial DNA is often the marker of choice for species identification, the unusual cytonuclear patterns in African elephants make nuclear markers more reliable. We therefore designed and utilized genetic markers for short nuclear DNA regions that contain fixed nucleotide differences between forest and savanna elephants. We used M13 forward and reverse sequences to increase the total length of PCR amplicons and to improve the quality of sequences for the target DNA. We successfully sequenced fragments of nuclear genes from dung samples of known savanna and forest elephants in the Democratic Republic of Congo, Ethiopia, and Namibia. Elephants at previously unexamined locations were found to have nucleotide character states consistent with their status as savanna or forest elephants. Using these and results from previous studies, we estimated that the short-amplicon nuclear markers could distinguish forest from savanna African elephants with more than 99% accuracy. Nuclear genotyping of museum, dung, or ivory samples will provide better-informed conservation management of Africa's elephants.
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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 | 0.000 | 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