Burying Dogs in Ancient Cis-Baikal, Siberia: Temporal Trends and Relationships with Human Diet and Subsistence Practices
Bibliographic record
Abstract
The first objective of this study is to examine temporal patterns in ancient dog burials in the Lake Baikal region of Eastern Siberia. The second objective is to determine if the practice of dog burial here can be correlated with patterns in human subsistence practices, in particular a reliance on terrestrial mammals. Direct radiocarbon dating of a suite of the region's dog remains indicates that these animals were given burial only during periods in which human burials were common. Dog burials of any kind were most common during the Early Neolithic (∼7-8000 B.P.), and rare during all other time periods. Further, only foraging groups seem to have buried canids in this region, as pastoralist habitation sites and cemeteries generally lack dog interments, with the exception of sacrificed animals. Stable carbon and nitrogen isotope data indicate that dogs were only buried where and when human diets were relatively rich in aquatic foods, which here most likely included river and lake fish and Baikal seal (Phoca sibirica). Generally, human and dog diets appear to have been similar across the study subregions, and this is important for interpreting their radiocarbon dates, and comparing them to those obtained on the region's human remains, both of which likely carry a freshwater old carbon bias. Slight offsets were observed in the isotope values of dogs and humans in our samples, particularly where both have diets rich in aquatic fauna. This may result from dietary differences between people and their dogs, perhaps due to consuming fish of different sizes, or even different tissues from the same aquatic fauna. This paper also provides a first glimpse of the DNA of ancient canids in Northeast Asia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".