A 9,000 Year History of Seal Hunting on Lake Baikal, Siberia: The Zooarchaeology of Sagan-Zaba II
Bibliographic record
Abstract
Sagan-Zaba II, a habitation site on the shore of Siberia's Lake Baikal, contains a record of seal hunting that spans much of the Holocene, making it one of the longest histories of seal use in North Asia. Zooarchaeological analyses of the 16,000 Baikal seal remains from this well-dated site clearly show that sealing began here at least 9000 calendar years ago. The use of these animals at Sagan-Zaba appears to have peaked in the Middle Holocene, when foragers used the site as a spring hunting and processing location for yearling and juvenile seals taken on the lake ice. After 4800 years ago, seal use declined at the site, while the relative importance of ungulate hunting and fishing increased. Pastoralists began occupying Sagan-Zaba at some point during the Late Holocene, and these groups too utilized the lake's seals. Domesticated animals are increasingly common after about 2000 years ago, a pattern seen elsewhere in the region, but spring and some summer hunting of seals was still occurring. This use of seals by prehistoric herders mirrors patterns of seal use among the region's historic and modern groups. Overall, the data presented in the paper demonstrate that Lake Baikal witnessed thousands of years of human use of aquatic resources.
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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 | 0.001 |
| 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".