{"id":"W4411534299","doi":"10.1145/3698061.3728392","title":"Explainable AI for the Arts 3 (XAIxArts3)","year":2025,"lang":"en","type":"article","venue":"","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Engineering and Physical Sciences Research Council","keywords":"Computer science; The arts; Artificial intelligence; Visual arts; Art","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":[],"consensus_categories":[],"category_scores_codex":[0.0005649293,0.0001288021,0.0001256191,0.0001033866,0.0005623861,0.0004069595,0.001392737,0.00005184171,0.00006679777],"category_scores_gemma":[0.0002094672,0.00008717324,0.00009660807,0.0006131823,0.00006534191,0.0006089055,0.0003076841,0.0001055254,0.0001754113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004988784,"about_ca_system_score_gemma":0.0001310392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001590662,"about_ca_topic_score_gemma":0.000130341,"domain_scores_codex":[0.9987504,0.00002610505,0.0002394046,0.0003752807,0.0001621718,0.0004466781],"domain_scores_gemma":[0.9980759,0.0007055119,0.00003783654,0.0009233399,0.0002065836,0.00005082381],"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":[0.000004881173,0.00002806898,0.00003069285,0.000009992753,0.0000132638,0.00000232791,0.0002165376,0.0004065126,0.000250595,0.8835369,0.08029781,0.03520247],"study_design_scores_gemma":[0.00008670582,0.00004638453,0.00004948055,0.0000131134,0.000007350062,0.000002308679,0.0004488126,0.1578794,0.07186175,0.1680958,0.6013718,0.0001370035],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.000192135,0.0002320593,0.921927,0.03580194,0.0008133394,0.0005003716,6.424801e-7,0.0002262843,0.04030617],"genre_scores_gemma":[0.7839254,0.00005710776,0.06020701,0.032656,0.0002379584,0.0008462794,0.000002086297,0.00002272957,0.1220455],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.86172,"threshold_uncertainty_score":0.4325476,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02823487514792491,"score_gpt":0.3179326312488757,"score_spread":0.2896977561009508,"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."}}