{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001776775,0.0001464091,0.0004912075,0.003625307,0.01320698,0.009965686,0.001449977,0.001699321,0.01403523],"category_scores_gemma":[0.01847526,0.0002112683,0.0003935927,0.006716926,0.006304095,0.002078483,0.002344397,0.002307989,0.0004512801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1133183,"about_ca_system_score_gemma":0.1241964,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.993433,"about_ca_topic_score_gemma":0.9957657,"domain_scores_codex":[0.9965282,0.0002386897,0.0001353097,0.0002756937,0.001672815,0.00114936],"domain_scores_gemma":[0.9869064,0.003096503,0.0008921845,0.0006713586,0.006873489,0.001560045],"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":[0.0003615489,0.0001364361,0.0769389,0.0001452126,0.00008916727,0.001035822,0.02214364,0.004897346,0.0006080917,0.760843,0.03893517,0.09386576],"study_design_scores_gemma":[0.0001202612,0.0001194036,0.3251315,0.0005911377,0.0001515947,0.0005411491,0.04044756,0.01442551,0.001890908,0.1057052,0.5106225,0.0002532309],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.5623586,0.002429939,0.0006627242,0.01094999,0.0001231858,0.0000652466,0.001314124,0.00005425076,0.4220419],"genre_scores_gemma":[0.9612662,0.000566981,0.0001621172,0.0002842461,0.00001961275,0.000009613957,0.0001453304,0.00001687766,0.03752893],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1133183,"threshold_uncertainty_score":0.8221853,"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."}}