{"id":"W4399917675","doi":"10.1145/3635636.3660763","title":"Explainable AI for the Arts 2 (XAIxArts2)","year":2024,"lang":"en","type":"article","venue":"Creativity and Cognition","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Engineering and Physical Sciences Research Council; UK Research and Innovation","keywords":"The arts; Manifesto; Sociology; Computer science; Engineering ethics; Visual arts; Engineering; Political science; 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":[0.0004191233,0.00009492842,0.00008237192,0.00005656505,0.0004225717,0.0006363162,0.0001693364,0.00004338399,0.0000283472],"category_scores_gemma":[0.0001081362,0.0000701286,0.00004881507,0.0002358181,0.00008419423,0.0009903061,0.00007194042,0.00009879837,0.0000702543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001750071,"about_ca_system_score_gemma":0.00004254647,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003638605,"about_ca_topic_score_gemma":0.00003505699,"domain_scores_codex":[0.9992386,0.0000343832,0.0001099304,0.000292656,0.0001151199,0.0002093177],"domain_scores_gemma":[0.9988995,0.000743593,0.00001965912,0.0001973791,0.00009415548,0.00004573305],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000015062,0.00004627304,0.00001788051,0.00008925747,0.00002777102,0.00001771109,0.001550947,0.0000299437,0.001212872,0.6328227,0.005464038,0.3587056],"study_design_scores_gemma":[0.0001193725,0.000220771,0.0001798767,0.000148597,0.00005762185,0.00004335368,0.0008270323,0.2817986,0.06913026,0.4712848,0.1759277,0.0002620336],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004817663,0.001156954,0.9798565,0.007152754,0.0002974255,0.0003690656,0.0000076833,0.0002037004,0.006138239],"genre_scores_gemma":[0.9964649,0.0001274327,0.001224709,0.0007216756,0.0001439834,0.0002208261,0.000005845232,0.000007544789,0.001083091],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9916472,"threshold_uncertainty_score":0.6136012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04589826887072394,"score_gpt":0.3127543293377939,"score_spread":0.2668560604670699,"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."}}