{"id":"W3195935978","doi":"10.1371/journal.pone.0255109","title":"Materials In Paintings (MIP): An interdisciplinary dataset for perception, art history, and computer vision","year":2020,"lang":"en","type":"article","venue":"arXiv (Cornell University)","topic":"Aesthetic Perception and Analysis","field":"Neuroscience","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Science Foundation of Sri Lanka; Natural Sciences and Engineering Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; National Science Foundation","keywords":"Painting; Depiction; Computer science; Stylized fact; Bounding overwatch; Perception; Artificial intelligence; Visual arts; Computer graphics (images); Computer vision; Art; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004893421,0.001879839,0.0008047766,0.003413201,0.001068964,0.001561623,0.001877918,0.001883551,0.01782881],"category_scores_gemma":[0.002460003,0.0004866098,0.001677948,0.004263787,0.0006290199,0.001229847,0.00248331,0.00157987,0.01547196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001197263,"about_ca_system_score_gemma":0.0008718387,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01093585,"about_ca_topic_score_gemma":0.03628208,"domain_scores_codex":[0.9992101,0.0001157255,0.00007599399,0.0002354951,0.0002532092,0.0001094274],"domain_scores_gemma":[0.9991273,0.0001906597,0.0001045394,0.0003106123,0.0001473684,0.0001195306],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005392508,0.00028639,0.008126782,0.00424841,0.0001914003,0.0007544493,0.0009233055,0.003123663,0.01056606,0.003763084,0.8582628,0.1092144],"study_design_scores_gemma":[0.0001392056,0.0001417892,0.05251845,0.000592985,0.00009230417,0.001579939,0.0009182009,0.006951731,0.006124233,0.003520072,0.927307,0.0001141643],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.03315647,0.00468117,0.008093823,0.0006925063,0.000404712,0.0003253745,0.9256802,0.008264069,0.01870169],"genre_scores_gemma":[0.03748921,0.001149752,0.01862591,0.0002224916,0.00007143735,0.0006683629,0.9352317,0.000680265,0.00586081],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01782881,"threshold_uncertainty_score":0.05964333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08956258765448703,"score_gpt":0.2385880955920086,"score_spread":0.1490255079375216,"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."}}