The Open Aurignacian Project: 3D scanning and the digital preservation of the Italian Paleolithic record
Bibliographic record
Abstract
Here, we introduce an open-access database of 3D models of stone tools (n = 2,016) from four Early Upper Paleolithic sequences excavated south of the Alps and along Peninsular Italy, including Grotta della Cala, Grotta di Castelcivita, Grotta di Fumane, and Riparo Bombrini. Available through four self-standing Zenodo repositories, these models enable in-depth analysis of core reduction procedures, reduction intensity, and shape variability. Unlike other repositories, this database has been actively used to address archaeological questions, providing a comprehensive demonstration of the use of 3D models in lithic analysis. The Open Aurignacian Project utilizes various scanning devices, including the Artec Spider, Artec Micro, and micro-computed tomography, with a focus on enhancing the reproducibility and accessibility of archaeological data. This paper presents the scanning methodology, dataset organization, and technical validation of the project, while also discussing the scientific potential of these data to foster cross-continental research collaboration. Our open-sharing initiative is designed to stimulate inter-regional studies of human behavioral evolution, offering new opportunities to address questions in Paleolithic studies through the FAIR principles.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".