Stable isotopic (δ13C and δ15N) characterization of key faunal resources from Norse period settlements in North Iceland.
Bibliographic record
Abstract
During the Viking Age, Norse peoples established settlements across the North Atlantic, colonizing the pristine \nand near-pristine landscapes of the Faroe Islands, Iceland, Greenland, and the short-lived Vinland settlement in Newfoundland. \nCurrent North Atlantic archaeological research themes include efforts to understand human adaptation and impact \nin these environments. For example, early Icelandic settlements persisted despite substantial environmental impacts and \nclimatic change, while the Greenlandic settlements were abandoned ca. AD 1450 in the face of similar environmental degradation. \nThe Norse settlers utilized both imported domestic livestock and natural fauna, including wild birds and aquatic \nresources. The stable isotope ratios of carbon and nitrogen (expressed as δ13C and δ15N) in archaeofaunal bones provide a \npowerful tool for the reconstruction of Norse economy and diet. Here we assess the δ13C and δ15N values of faunal and floral \nsamples from sites in North Iceland within the context of Norse economic strategies. These strategies had a dramatic effect \nupon the ecology and environment of the North Atlantic islands, with impacts enduring to the present day.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 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".