Ethiopia: between Sub‐Saharan Africa and Western Eurasia
Bibliographic record
Abstract
Summary Ethiopia is central to population genetic studies investigating the out of Africa expansion of modern humans, as shown by Y chromosome and mtDNA studies. To address the level of genetic differentiation within Ethiopia, and its relationship to Sub‐Saharan Africa and Eurasia, we studied an 8kb segment of the X‐chromosome from 72 chromosomes from the Amhara, Oromo and Ethiopian Jews, and compared these results with 804 chromosomes from Middle Eastern, African, Asian and European populations, and 22 newly typed Saharawi. Within Ethiopia the two largest ethnic groups, the Amhara and Oromo, were not found to be statistically distinct, based on an exact test of haplotype frequencies. The Ethiopian Jews appear as an admixed population, possibly of Jewish origin, though the data remain equivocal. There is evidence of a close relationship between Ethiopian and Yemenite Jews, likely a result of indirect gene flow. Within an African and Eurasian context, the distribution of alleles of a variable Tn repeat, and the spread of haplotypes containing Africa‐specific alleles, provide evidence of a genetic continuity from Sub‐Saharan Africa to the Near East, and furthermore suggest that a bottleneck occurred in Ethiopia associated with an out of Africa expansion. Ethiopian genetic heterogeneity, as evidenced by principal component analysis of haplotype frequencies, most likely resulted from periods of subsequent admixture. While these results are from the analysis of one locus, we feel that in association with data from other marker systems they add a complementary perspective on the history of Ethiopia.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".