Zaraa Uul: An archaeological record of Pleistocene-Holocene palaeoecology in the Gobi Desert
Bibliographic record
Abstract
Environmentally-based archaeological research at Zaraa Uul, including zooarchaeology, phytolith analysis, and radiocarbon dating, is the first of its kind in Mongolia and presents critical new insight on the relationship between periods of occupational intensity and climatic amelioration from the earliest anatomically modern humans to the adoption of pastoralism. The palaeoenvironmental and faunal record of Zaraa Uul show that Early-Middle Holocene hydrology and species distributions were distinct from all other periods of human occupation. Holocene hunter-gatherers inhabited an ecosystem characterized by extensive marshes, riparian shrub and arboreal vegetation along the hill slopes and drainages. The exploitation of species associated with riparian and wetland settings supports the hypothesis of, but suggests an earlier timing for, oasis-based logistical foraging during the Early-Middle Holocene of arid Northeast Asia. The onset of wetter conditions at 8500 cal BP agrees with other regional studies, but multiple lines of evidence present the first integrated field- and laboratory-based record of human-environment relationships in arid East Asia during the Holocene Climatic Optimum. We compare it to Late Pleistocene climatic amelioration, and highlight specific responses of the hydrological, vegetative and faunal communities to climate change in arid Northeast Asia.
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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) | 0.001 | 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".