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Record W4396903688 · doi:10.1080/00934690.2024.2348854

Models of Grinding Stone Manufacture, Use, and Discard from Tigrai, Ethiopia: Opportunities for Cultural Comparisons and Implications for Usewear Analysis

2024· article· en· W4396903688 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Field Archaeology · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicForensic Anthropology and Bioarchaeology Studies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsGrindingArchaeologyStone toolEngineeringHistoryMechanical engineering

Abstract

fetched live from OpenAlex

Grinding stones are a worldwide technology, instrumental in processing food as far back as the African Middle Stone Age. Research interest in grinding stones, and the usewear on their surfaces, has grown in the last few decades. Models of grinding stone manufacture, use, and discard provide a reference for cross-cultural comparisons of practices and guide methodologies in planning usewear analysis based on kinetics. In Ethiopia, traditional knowledge of grinding stones is still accessible, and grinding stones remain in use. The models developed through interviews with, and observations of, local practitioners show processes and behaviors but also decisions made at various stages. Particular behaviors and decisions have impacts on tool wear.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.302
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.005
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.188
GPT teacher head0.346
Teacher spread0.158 · 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