High altitude hunting, climate change, and pastoral resilience in eastern Eurasia
Bibliographic record
Abstract
The transition from hunting to herding transformed the cold, arid steppes of Mongolia and Eastern Eurasia into a key social and economic center of the ancient world, but a fragmentary archaeological record limits our understanding of the subsistence base for early pastoral societies in this key region. Organic material preserved in high mountain ice provides rare snapshots into the use of alpine and high altitude zones, which played a central role in the emergence of East Asian pastoralism. Here, we present the results of the first archaeological survey of melting ice margins in the Altai Mountains of western Mongolia, revealing a near-continuous record of more than 3500 years of human activity. Osteology, radiocarbon dating, and collagen fingerprinting analysis of wooden projectiles, animal bone, and other artifacts indicate that big-game hunting and exploitation of alpine ice played a significant role during the emergence of mobile pastoralism in the Altai, and remained a core element of pastoral adaptation into the modern era. Extensive ice melting and loss of wildlife in the study area over recent decades, driven by a warming climate, poaching, and poorly regulated hunting, presents an urgent threat to the future viability of herding lifeways and the archaeological record of hunting in montane zones.
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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 | 0.000 | 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) | 0.000 | 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".