{"id":"W7024221712","doi":"","title":"The Rise of Machines: Patenting Inventions Generated by Artificial Intelligence in Canada","year":2022,"lang":"en","type":"article","venue":"eYLS (Yale Law School)","topic":"Law, AI, and Intellectual Property","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Patentability; Context (archaeology); Statutory law; Incentive; Patentable subject matter; Invention; Database transaction; Patent law","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":[0.003243707,0.0002213558,0.0003859118,0.003158103,0.01920758,0.009124728,0.001471426,0.003240047,0.006089781],"category_scores_gemma":[0.01250132,0.0003795871,0.0005256983,0.004178601,0.00716896,0.002980439,0.002158105,0.003398062,0.0002435984],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.147165,"about_ca_system_score_gemma":0.2246663,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9946647,"about_ca_topic_score_gemma":0.9957927,"domain_scores_codex":[0.994138,0.0003720947,0.0001373417,0.0004278254,0.002762566,0.002162084],"domain_scores_gemma":[0.9928769,0.00254435,0.000335648,0.0002819104,0.003050206,0.0009108791],"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":[0.0001154346,0.0000629591,0.01198977,0.0001591937,0.00002640803,0.001322862,0.007426441,0.001503236,0.001024338,0.8841025,0.03448971,0.05777718],"study_design_scores_gemma":[0.0001502781,0.000134129,0.0695178,0.0004969138,0.0001854052,0.0006166542,0.01503804,0.009832473,0.003489501,0.08860225,0.8116481,0.000288465],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3067957,0.008793887,0.005346073,0.09175248,0.0005354431,0.0003322651,0.001037392,0.00013413,0.5852727],"genre_scores_gemma":[0.9230052,0.004522123,0.002267331,0.004653315,0.00006732425,0.00004168316,0.0002444243,0.00002512166,0.0651734],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.147165,"threshold_uncertainty_score":0.9891677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02424339005482008,"score_gpt":0.2275341017449953,"score_spread":0.2032907116901752,"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."}}