{"id":"W4411455735","doi":"10.1038/s41597-025-05330-z","title":"The Open Aurignacian Project: 3D scanning and the digital preservation of the Italian Paleolithic record","year":2025,"lang":"en","type":"article","venue":"Scientific Data","topic":"Pleistocene-Era Hominins and Archaeology","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Università degli Studi di Ferrara; Eberhard Karls Universität Tübingen; European Commission; Social Sciences and Humanities Research Council of Canada; Université de Montréal; Università degli Studi di Siena; Deutsche Forschungsgemeinschaft; Università degli Studi di Genova; Ministero della cultura","keywords":"Aurignacian; Upper Paleolithic; Archaeology; 3d scanning; Middle Paleolithic; 3d model; Geography; Focus (optics); Computer science; Geology; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003106565,0.000721263,0.0004315932,0.009781173,0.0009750521,0.002873561,0.001228373,0.0005769251,0.006773283],"category_scores_gemma":[0.005369315,0.0003470219,0.0006122185,0.008905452,0.001846488,0.001520201,0.004619207,0.0004609482,0.002416498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008621575,"about_ca_system_score_gemma":0.001973606,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01151085,"about_ca_topic_score_gemma":0.01937107,"domain_scores_codex":[0.9982868,0.0004819227,0.0001474527,0.0003668806,0.0005631626,0.0001538661],"domain_scores_gemma":[0.9955186,0.0008315944,0.0006667109,0.002294455,0.0003734741,0.000315117],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008902797,0.000154024,0.1599642,0.001955879,0.0002591954,0.001150323,0.0105344,0.003037652,0.007728009,0.01673587,0.08402795,0.7135622],"study_design_scores_gemma":[0.0000691338,0.0001038508,0.4000839,0.0008721161,0.0001514206,0.002269491,0.004051456,0.003347056,0.004416677,0.009275473,0.5752378,0.0001216203],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.5472028,0.01186361,0.08363978,0.002810896,0.0005567948,0.000866344,0.2647803,0.007796292,0.08048314],"genre_scores_gemma":[0.6295539,0.004296239,0.1364415,0.0002854112,0.0004435505,0.002005327,0.2170762,0.001844175,0.008053752],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.01151085,"threshold_uncertainty_score":0.02288771,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06706645450932129,"score_gpt":0.3528548644334915,"score_spread":0.2857884099241702,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}