Mongolians in the Genetic Landscape of Central Asia: Exploring the Genetic Relations among Mongolians and Other World Populations
Bibliographic record
Abstract
Genetic data on North and Central Asian populations are underrepresented in the literature, especially for autosomal markers. In the present study we used 812 single nucleotide polymorphisms (SNPs) distributed across all the human autosomes and extensively studied at Yale to examine the affinities of two recently collected samples of populations: rural and cosmopolitan Mongolians from Ulaanbaatar and nomadic, Turkic-speaking Tsaatan from Mongolia near the Siberian border. We compare these two populations with each other and with a global set of populations and discuss their relationships to New World populations. Specifically, we analyze data on 521 autosomal loci (single SNPs and multi-SNP haplotypes) studied in 57 populations representing all the major geographical regions of the world. We conclude that these North and Central Asian populations are genetically distinct from all other populations in our study and may be close to the ancestral lineage leading to the New World populations.
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".