Archaic Lineages in the History of Modern Humans
Bibliographic record
Abstract
An important question in the ongoing debate on the origin of Homo sapiens is whether modern human populations issued from a single lineage or whether several, independently evolving lineages contributed to their genetic makeup. We analyzed haplotypes composed of 35 polymorphisms from a segment of the dystrophin gene. We find that the bulk of a worldwide sample of 868 chromosomes represents haplotypes shared by different continental groups. The remaining chromosomes carry haplotypes specific for the continents or for local populations. The haplotypes specific for non-Africans can be derived from the most frequent ones through simple recombination or a mutation. In contrast, chromosomes specific for sub-Saharan Africans represent a distinct group, as shown by principal component analysis, maximum likelihood tree, structural comparison, and summary statistics. We propose that African chromosomes descend from at least two lineages that have been evolving separately for a period of time. One of them underwent range expansion colonizing different continents, including Africa, where it mixed with another, local lineage represented today by a large fraction of African-specific haplotypes. Genetic admixture involving archaic lineages appears therefore to have occurred within Africa rather than outside this continent, explaining greater diversity of sub-Saharan populations observed in a variety of genetic systems.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".