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Record W2097188835 · doi:10.1002/gea.10031

Lithic raw material usages during the Middle Stone Age at Dakhleh Oasis, Egypt

2002· article· en· W2097188835 on OpenAlexaff
Alicia L. Hawkins, Maxine R. Kleindienst

Bibliographic record

VenueGeoarchaeology · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicPleistocene-Era Hominins and Archaeology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRaw materialMiddle Stone AgeOil shaleArchaeologyGeologyGeographyRaw dataMining engineeringPaleontologyComputer scienceEcologyBiology

Abstract

fetched live from OpenAlex

Abstract Dakhleh Oasis, the largest of the Egyptian Western Desert, presents an opportunity for diachronic study of lithic raw material preferences during the Middle Stone Age (MSA) of the Eastern Sahara. Archaeological aggregates and raw material sources are exposed and easily mapped. Diverse and abundant lithic raw materials derive from sandstone, shale, and limestone sources and are also found in secondary geological contexts. Three main raw materials were used, and there was strong preference for one of these: Tarawan chert. Easily available only in the north‐central oasis, this material was transported substantial distances even when other materials that were known and used by MSA peoples could be found closer at hand. There is little evidence for use of raw materials exogenous to Dakhleh Oasis. This pattern of usage does not appear to change from the older MSA units to the Aterian Dakhleh Unit. © 2002 Wiley Periodicals, Inc.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.045
GPT teacher head0.273
Teacher spread0.228 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations11
Published2002
Admission routes1
Has abstractyes

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