{"id":"W4382538634","doi":"10.2139/ssrn.4493517","title":"The Copyrightability of Art Generated by Artificial Intelligence in Canada","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Law, AI, and Intellectual Property","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Artificial intelligence; Political science; Psychology; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002129447,0.0001105639,0.0001562542,0.00005681018,0.0002426497,0.00007701974,0.001055063,0.00003537292,0.00002687604],"category_scores_gemma":[0.0001808462,0.00006865743,0.00004982544,0.0008803724,0.0001020609,0.0001825403,0.00009547838,0.0008883669,0.00004014863],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001290396,"about_ca_system_score_gemma":0.009045169,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1267966,"about_ca_topic_score_gemma":0.8556704,"domain_scores_codex":[0.9972522,0.0001882292,0.00047554,0.000213842,0.0003762284,0.001493934],"domain_scores_gemma":[0.9992075,0.0001980935,0.0001135143,0.0002885162,0.0001236929,0.00006865674],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001525312,0.0001586698,0.0008978687,0.00001308474,0.0001578783,0.00002098971,0.0009381152,0.001413688,0.008044431,0.4226538,0.05613026,0.5094187],"study_design_scores_gemma":[0.0002018715,0.0004660388,0.0001573194,0.0000219716,0.000007392077,0.0001110857,0.001660907,0.3413592,0.03693558,0.5953515,0.02334536,0.0003817766],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4712133,0.004704361,0.504871,0.01285731,0.002411762,0.0005285079,0.0000129321,0.0001170694,0.003283712],"genre_scores_gemma":[0.9971532,0.001997032,0.00003700544,0.00009002192,0.00005163831,0.000003616609,0.000001953104,0.000006747827,0.0006587433],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7288738,"threshold_uncertainty_score":0.9965726,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01460518254398866,"score_gpt":0.2226508514441184,"score_spread":0.2080456689001297,"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."}}