A Typo-technological Analysis of Lithic Assemblages from Ghar-e Khar Cave, Bisotun
Bibliographic record
Abstract
This paper presents a typo-technological analysis of the lithic assemblages from the 1965 excavation of Khar Cave in the mountainous region of Central Zagros, Iran. Khar Cave is one of the rare excavated Paleolithic sites in Zagros region with a stratified sequence encompassing archaeological materials from both MIS 2 and MIS 3. The research is based on the typo-technological characteristics of artifacts from both parts of the Khar Cave lithic assemblage, which are stored in the National Museum of Iran and in Montreal University, and have not been properly studied in terms of technology. The paper addresses the issue of the Middle to Upper Paleolithic transition in Zagros; technological characteristics of Baradostian/Zagros Aurignacian industries; and the possibility of industrial evolution from the late Baradostian to the early Zarzian. Despite the small size of the assemblage, the analysis illustrates a sequence of changes and continuity in core-reduction strategies and tool-production in Khar Cave, beginning in the Late Middle Paleolithic to Epipaleolithic. However, from the current state of data, the paper concludes that our technological data supporting the hypothesis of Middle-to-Upper-Paleolithic continuity in Zagros are insufficient, and we can neither confirm nor reject the possibility of a gradual transition in this region.
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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 | 0.008 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".