Exploring models of human migration to the Japanese archipelago using genome-wide genetic data
Bibliographic record
Abstract
The origins of people in the Japanese archipelago are of long-standing interest among anthropologists, archeologists, linguists, and historians studying the history of Japan. While the ‘dual-structure’ model proposed by Hanihara in 1991 has been considered the primary working hypothesis for three decades, recent advances in DNA typing and sequencing technologies provide an unprecedented amount of present-day and ancient human nuclear genome data, which enable us to refine or extend the dual-structure model. In this review, we summarize recent genome sequencing efforts of present-day and ancient people in Asia, mostly focusing on East Asia, and we discuss the possible migration routes and admixture patterns of Japanese ancestors. We also report on a meta-analysis we performed by compiling publicly available datasets to clarify the genetic relationships of present-day and ancient Japanese populations with surrounding populations. Because the ancient genetic data from the Japanese archipelago have not yet been fully analyzed, we have to corroborate models of prehistoric human movement using not only new genetic data but also linguistic and archeological data to reconstruct a more comprehensive history of the Japanese people.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".