Late Pleistocene to late Holocene palaeoecology and human foraging at Kuumbi Cave, Zanzibar Island
Bibliographic record
Abstract
Background Climate change played a major role in shaping regional human-environment interactions in Africa during the late Pleistocene-Holocene, but this topic has not been exhaustively studied, particularly in eastern Africa. While there is growing evidence that the coastal and island settings in this region played a critical role in human evolution, combined archaeological and palaeoenvironmental studies have tended to focus on the arid interior and show the dominance of grasslands with patches of closed and open woodlands during the last 20,000 years. Methods Here, we present stable carbon and oxygen isotope analyses of zooarchaeological remains (n = 229) recovered from Kuumbi Cave, Zanzibar Island, spanning the last glacial period and the Holocene (20,000 to 500 cal. BP). Results Our data demonstrate that the vicinity of Kuumbi Cave was consistently covered by mosaic habitats, dominated by forests and small patches of open woodland and grassland. The inhabitants of Kuumbi Cave exploited these diverse tropical habitats even after the regional arrival of agriculture. Discussion We suggest that the stable coastal forest mosaic habitats acted as a refugium for foragers during glacial periods and that the Iron Age inhabitants of Kuumbi Cave were not food producers migrating from the interior, but rather Indigenous foragers interacting with food production.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".