Archives of human-dog relationships: Genetic and stable isotope analysis of Arctic fur clothing
Bibliographic record
Abstract
Among Indigenous populations of the Arctic, domestic dogs (Canislupus familiaris) were social actors aiding in traction and subsistence activities. Less commonly, dogs fulfilled a fur-bearing role in both the North American and Siberian Arctic. Examples of garments featuring dog skins were collected during the 19th-20th centuries and are now curated by the National Museum of Denmark. We sequenced the mitochondrial genomes of macroscopically identified dog skin garments. We conducted stable carbon and nitrogen isotope ratio analysis of the dog furs and of fur samples from contemporaneous pelts of Arctic (C. lupus arctos) and grey (C. lupus) wolves. Despite the presence of biocides used to protect the fur clothing during storage, we extracted well-preserved DNA using a minimally-invasive sampling protocol. Unexpectedly, the mtDNA genomes of one-third of the samples were consistent with wild taxa, rather than domestic dogs. The strong marine component in the diets of North American dogs distinguished them from Greenland and Canadian wolves, but Siberian dogs consumed diets that were isotopically similar to wild species. We found that dog provisioning practices were variable across the Siberian and North American Arctic, but in all cases, involved considerable human labor.
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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 | 0.000 |
| 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".