{"id":"W2298718905","doi":"10.4000/insitu.12743","title":"Mouler, tirer, modifier, mouler à nouveau. Rodin et le moulage","year":2016,"lang":"fr","type":"article","venue":"In Situ","topic":"Cultural Insights and Digital Impacts","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Musée de la Civilisation","funders":"","keywords":"Art; Humanities","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003546566,0.0004091714,0.0004031081,0.0001489824,0.0001213033,0.0009876748,0.0008197257,0.0002871688,0.0001218222],"category_scores_gemma":[0.0001651628,0.000269743,0.0001834298,0.0005354534,0.0002716197,0.005356786,0.0005638194,0.0002698653,0.001335411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001797542,"about_ca_system_score_gemma":0.00024005,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00187524,"about_ca_topic_score_gemma":0.0009013876,"domain_scores_codex":[0.9972801,0.0001523338,0.0004518777,0.0007567725,0.0004572565,0.0009016937],"domain_scores_gemma":[0.9982809,0.0002032276,0.0001413718,0.0008227244,0.0001522224,0.0003995673],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002743289,0.0006454983,0.0001652957,0.00003749559,0.00002926107,0.0005706583,0.002488854,0.0002035443,0.06282099,0.801617,0.04043205,0.09096194],"study_design_scores_gemma":[0.005172528,0.0004921025,0.01108972,0.001041999,0.00002763373,0.000451414,0.0002330199,0.005020101,0.08258435,0.1102018,0.7816018,0.002083543],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3525029,0.01185778,0.02003525,0.08777887,0.004751297,0.0006010788,0.00009170326,0.0003035296,0.5220776],"genre_scores_gemma":[0.8811783,0.0003809883,0.001374756,0.002051094,0.0002197511,0.00001226267,0.000006097165,0.00002772016,0.1147491],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7411698,"threshold_uncertainty_score":0.9999755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2098605485114348,"score_gpt":0.3167429480263985,"score_spread":0.1068823995149636,"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."}}