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CONTINUITY AND CHANGE IN THE LATE PLEISTOCENE LITHIC INDUSTRIES OF THE CENTRAL ZAGROS: A TYPO-TECHNOLOGICAL ANALYSIS OF LITHIC ASSEMBLAGES FROM GHAR-E KHAR CAVE, BISOTUN, IRAN

2016· article· en· W2460380167 on OpenAlexaboutno aff
Sonia Shidrang, Fereidoun Biglari, Jean-Guillaume Bordes, Jacques Jaubert

Bibliographic record

VenueArchaeology Ethnology and Anthropology of Eurasia · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicPleistocene-Era Hominins and Archaeology
Canadian institutionsnot available
Fundersnot available
KeywordsCaveAurignacianUpper PaleolithicMiddle PaleolithicAssemblage (archaeology)Lithic technologyArchaeologyPleistoceneSequence (biology)GeologyExcavationGeographyBlade (archaeology)Paleontology

Abstract

fetched live from OpenAlex

The paper presents a typo-technological analysis of the lithic assemblages from the 1965 excavation of Khar cave in mountainous region of Central Zagros, Iran. Khar cave is one of the rare excavated Paleolithic sites in Zagros region with a stratifi ed sequence encompassing archaeological materials from both MIS 2 and MIS 3. The research is based on typo-technological characteristics of artifacts from the both parts of the Khar cave lithic assemblage, which are stored in the National Museum of Iran and in the Montreal University and have not been properly studied in terms of technology. The paper addresses the issue of 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 tools production in Khar cave, beginning from Late Middle Paleolithic to Epipaleolithic. However based on the current state of data, the paper reaches a conclusion that our technological data supporting the hypothesis of Middle to Upper Paleolithic continuity in Zagros are insuffi cient and we can neither confi rm nor reject the possibility of a gradual transition in this region.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.188
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.060
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.048
GPT teacher head0.324
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations29
Published2016
Admission routes1
Has abstractyes

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