Using mechanical experiments to study Ground Stone Tool use: exploring the formation of percussive and grinding wear traces on limestone tools
Bibliographic record
Abstract
Ground Stone Tools (GST) have been identified in several Levantine archaeological sites dating to the Middle Paleolithic. These tools, frequently made of limestone, are often interpreted based on their morphology and damage as having been used for knapping flint, and sometimes for breaking animal bones or processing vegetal materials as well. However, the lack of experimental referential collections on limestone is a major obstacle for the identification of diagnostic traces on these types of tools and raw material. In this sense, the understanding of the specific function of these GST and the association between tool types and activity often remains unknown or merely speculative.Recent discoveries at the site of Nesher Ramla revealed one of the largest Middle Paleolithic assemblages of limestone GST. Our use-wear analysis has identified several types of both macro and micro-wear traces on different tools. Such diversity highlights the need for developing an experimental reference collection that can enable detailed comparison between experimental and archaeological use-wear evidence.In this paper, we present the results of mechanical experiments specially designed to understand and quantify major characteristics of macro and micro use-wear traces on limestone GST as a result of three main activities: 1) animal bone breaking, 2) flint knapping and 3) grinding acorns. This study pursues three main goals: a) improving our ability to distinguish natural from anthropogenic alterations on limestone; b) identifying and characterizing differences between wear-traces (macro and micro) produced by different activities, and c) building a reference collection for thorough comparisons of use-wear and residues on archaeological tools.Our results indicate that it is possible not only to identify anthropogenic alterations but also to specifically distinguish the use-wear traces formed on limestone as result of percussive activities of bone and flint. This is shown by controlled experiments allowing variables other than the worked material to remain constant. This study aims to contribute towards establishing an experimental and multi-scale library of use-wear traces on limestone.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".