Ancient human parallel lineages within North America contributed to a coastal expansion
Bibliographic record
Abstract
Founder effects in modern populations The genomes of ancient humans can reveal patterns of early human migration (see the Perspective by Achilli et al. ). Iceland has a genetically distinct population, despite relatively recent settlement (∼1100 years ago). Ebenesersdóttir et al. examined the genomes of ancient Icelandic people, dating to near the colonization of Iceland, and compared them with modernday Icelandic populations. The ancient DNA revealed that the founders had Gaelic and Norse origins. Genetic drift since the initial settlement has left modern Icelanders with allele frequencies that are distinctive, although still skewed toward those of their Norse founders. Scheib et al. sequenced ancient genomes from the Channel Islands of California, USA, and Ontario, Canada. The ancient Ontario population was similar to other ancient North Americans, as well as to modern Algonquian-speaking Native Americans. In contrast, the California individuals were more like groups that now live in Mexico and South America. It appears that a genetic split and population isolation likely occurred during the Ice Age, but the peoples remixed at a later date. Science , this issue p. 1028 , p. 1024 ; see also p. 964
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".