Bibliographic record
Abstract
• Evidence of different use-wear on the same grinding surface, even within close proximity. • Evidence of use-wear from both ethnographic and archaeological tools. • Kinetics witnessed in modern practises to explain resultant kinematics, use-wear observed. • Suggestions for systematic sampling for comparison between tools. • Discussion on possible field work limitations that can be encountered. Mapping out the surface of a grinding stone and selecting regions for use-wear analysis could pick up the effects of varying kinetics used in grinding. Observing the kinetics of the grinders in the modern villages of Tigrai, northern Ethiopia, revealed important information about potential use-wear, and lack thereof. While some sections are subject to little or no friction, other sections have concentrated pressure and higher friction which cause use-wear. Resharpening of the surface also has an affect on wear. This results in tribological effects and resulting kinematics varying across the surface. While a previous publication has described the kinetics used in grinding, this paper will provide examples of different use-wear patterns observed on the same working surface but from different areas. Methodological suggestions are made for analyses on grinding stone surfaces to understand the use-wear of past kinetics of use and the resulting kinematics.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".