Composition of the founding population of Iceland: Biological distance and morphological variation in early historic Atlantic Europe
Bibliographic record
Abstract
We examined the composition of the founding population of Iceland through the study of morphological traits in skeletons from Iceland, Ireland, Norway, and Greenland. This is the first study to address this issue from the Settlement Period of Iceland and contemporary samples from Ireland. We pose the following questions: 1) Was the founding population of Iceland of mixed or homogeneous origin? 2) Is there evidence for a significant Irish cohort in the founding population, as suggested in medieval Icelandic literature? Analysis of biodistance revealed that both Settlement Age and later samples from Iceland showed a greater degree of phenetic similarity to contemporary Viking Age Norwegians than to samples obtained from early medieval Ireland. Analysis of among-individual morphological variation showed that the Settlement Age population of Iceland did not exhibit an increase in variation in comparison to other populations in the sample, suggesting a relatively homogenous origin. However, estimation of admixture between the Irish and Norwegian populations indicated that 66% of the Icelandic settlers were of Norwegian origin. Comparison of the Icelandic samples to hybrid samples produced by resampling the Viking Age Norwegian and early medieval Irish samples revealed that the Icelandic samples are much closer to the Norwegian samples than expected, based on a 66:34 mixture of Norwegian and Irish settlers. We conclude that the Settlement Age population of Iceland was predominantly (60-90%) of Norwegian origin. Although this population was relatively homogenous, our results do not preclude significant contributions from Ireland as well as other sources not represented in our analysis.
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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 | 0.001 |
| 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".