Mugharat an-Nachcharini: A specialized sheep-hunting camp reveals high-altitude habitats in the earliest Neolithic of the Central Levant
Bibliographic record
Abstract
The earliest Neolithic of southwest Asia is generally perceived and portrayed as a period of emerging economic practices that anticipated full-fledged food-producing economies. This first Neolithic, however, can also be seen as the last gasp of an earlier way of life that remained fundamentally Epipaleolithic in character. While people at this time had begun to cultivate some of the plant foods gathered in preceding periods, and to live for lengthy periods in sites with substantial architecture, they also relied on hunting for a significant portion of their diet and logistical movement across landscapes to exploit diverse environments. The objective of our research on Nachcharini Cave, the only excavated early Neolithic site in the high mountains of northeastern Lebanon, is to evaluate its role in a form of logistical organization not well attested at other sites in the Levant during this period. On the basis of material that Bruce Schroeder excavated in the 1970s, we present here for the first time analyses of faunal and lithic evidence from Nachcharini Cave, along with new radiocarbon dates that place the major occupation layer of the site firmly in the earliest Neolithic. We conclude that Nachcharini was a short-term hunting camp that was periodically used over some two centuries.
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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 | 0.001 |
| 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".