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Record W2622806985 · doi:10.1007/s10437-017-9254-2

Middle Stone Age Technology and Cultural Evolution at Magubike Rockshelter, Southern Tanzania

2017· article· en· W2622806985 on OpenAlexafffund
J. Jeffrey Werner, Pamela R. Willoughby

Bibliographic record

VenueAfrican Archaeological Review · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicPleistocene-Era Hominins and Archaeology
Canadian institutionsUniversity of Alberta
FundersMinistry of Natural Resources and TourismTanzania Commission for Science and TechnologySocial Sciences and Humanities Research Council of CanadaUniversity of Dar es SalaamWilliams College
KeywordsMiddle Stone AgeTanzaniaLithic technologyArchaeologyTypologyStone AgeGeographyLater Stone AgeArchaeological recordStone toolPleistocene

Abstract

fetched live from OpenAlex

This paper contributes new information to the body of evidence for Middle Stone Age tool-use in Tanzania. Magubike rockshelter is located in an archaeologically unexplored region of the south-central part of the country, and thus fills a significant geographical gap between sites further to the north and those to the south in Zambia and Mozambique. Early analysis of a portion of the lithic materials demonstrates parallel changes in lithic reduction intensity, raw material preference and typology. This article explores possible explanations for this pattern, including the possibility that they reflect changes to local environment, and suggests avenues for future research.

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)0.000
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 score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

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

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 head0.052
GPT teacher head0.321
Teacher spread0.269 · 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

Citations39
Published2017
Admission routes2
Has abstractyes

Explore more

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