{"id":"W4391854717","doi":"10.3386/w32106","title":"Copyright Policy Options for Generative Artificial Intelligence","year":2024,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Law, AI, and Intellectual Property","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Generative grammar; Computer science; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02134191,0.0005670632,0.0005587094,0.001585875,0.002702533,0.009356438,0.002738551,0.00576132,0.0238964],"category_scores_gemma":[0.06355827,0.0004619379,0.001090414,0.001322925,0.01100489,0.01599575,0.004538723,0.006735276,0.002083385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004540431,"about_ca_system_score_gemma":0.004199156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001821672,"about_ca_topic_score_gemma":0.002027904,"domain_scores_codex":[0.9904312,0.004755391,0.0003412444,0.001003033,0.002656968,0.0008120477],"domain_scores_gemma":[0.9437666,0.03704488,0.00210299,0.01282887,0.002925987,0.001330714],"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":[0.0000124442,0.00002286829,0.0001510094,0.00001350779,0.000004378982,0.00002101878,0.0001088693,0.00192731,0.0001174974,0.9891564,0.0012241,0.007240635],"study_design_scores_gemma":[0.00001575365,0.0000167279,0.000188235,0.00004948468,0.000007260785,0.00003814654,0.00009579517,0.008058771,0.0003320811,0.9747269,0.0164593,0.00001152273],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.0922882,0.003123244,0.2534606,0.06261536,0.0008077534,0.0002400088,0.0002422481,0.0006297645,0.5865927],"genre_scores_gemma":[0.9319933,0.001290198,0.02577328,0.004561261,0.0006554171,0.0003336463,0.0001154475,0.0001944991,0.03508298],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0238964,"threshold_uncertainty_score":0.1128681,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5584127772579706,"score_gpt":0.5503577004278836,"score_spread":0.008055076830086993,"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."}}