An in-depth analysis of the mitochondrial phylogenetic landscape of Cambodia
Bibliographic record
Abstract
Cambodia harbours a variety of human aboriginal populations that have scarcely been studied in terms of genetic diversity of entire mitochondrial genomes. Here we present the matrilineal gene pool of 299 Cambodian refugees from three different ethnic groups (Cham, Khmer, and Khmer Loeu) deriving from 16 Cambodian districts. After establishing a DNA-saving high-throughput strategy for mitochondrial whole-genome Sanger sequencing, a HaploGrep based workflow was used for quality control, haplogroup classification and phylogenetic reconstruction. The application of diverse phylogenetic algorithms revealed an exciting picture of the genetic diversity of Cambodia, especially in relation to populations from Southeast Asia and from the whole world. A total of 224 unique haplotypes were identified, which were mostly classified under haplogroups B5a1, F1a1, or categorized as newly defined basal haplogroups or basal sub-branches of R, N and M clades. The presence of autochthonous maternal lineages could be confirmed as reported in previous studies. The exceptional homogeneity observed between and within the three investigated Cambodian ethnic groups indicates genetic isolation of the whole population. Between ethnicities, genetic barriers were not detected. The mtDNA data presented here increases the phylogenetic resolution in Cambodia significantly, thereby highlighting the need for an update of the current human mtDNA phylogeny.
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.
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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".