{"id":"W4324144845","doi":"10.21900/j.median.v19i1.1174","title":"The Medium is the Data Set: Art and AI","year":2023,"lang":"en","type":"article","venue":"Media-N","topic":"Art, Technology, and Culture","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Set (abstract data type); Data set; Computer science; Information retrieval; Artificial intelligence; Programming language","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002830168,0.00007439496,0.00006940024,0.00001687765,0.0007340896,0.0001250988,0.0005144097,0.00004306024,0.0005387646],"category_scores_gemma":[0.0001052466,0.00003264366,0.00001677636,0.00002839914,0.0006165333,0.00009322394,0.0002765787,0.0001859737,0.0007142392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002755706,"about_ca_system_score_gemma":0.0000126367,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003070722,"about_ca_topic_score_gemma":0.004935744,"domain_scores_codex":[0.9994272,0.00002023421,0.00008609827,0.0001478611,0.0001364796,0.0001821531],"domain_scores_gemma":[0.9992254,0.0001537984,0.00002433682,0.0005439719,0.00002596774,0.00002654176],"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":[0.000001492688,0.0000024563,0.00005835337,0.000002763253,0.00001665209,0.000002812597,0.03161937,1.850707e-8,0.000005009128,0.02577413,0.9393352,0.003181703],"study_design_scores_gemma":[0.00006587193,0.000009230542,0.0002538337,0.000004636669,0.00001573597,0.000002087302,0.02133887,0.00006925212,0.00002703099,0.008753167,0.9694082,0.00005214998],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.03409075,0.00596495,0.000009761816,0.8287392,0.004705385,0.000576863,0.00110608,0.001123988,0.123683],"genre_scores_gemma":[0.6827182,0.006673583,0.00001408262,0.02796231,0.006949545,0.0001186354,0.0008956837,0.00007195665,0.274596],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.8007769,"threshold_uncertainty_score":0.9180338,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06156869356990351,"score_gpt":0.2642160478109559,"score_spread":0.2026473542410524,"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."}}