{"id":"W3001278417","doi":"10.1007/s40319-020-00908-z","title":"The Intersection Between AI and IP: Conflict or Complementarity?","year":2020,"lang":"en","type":"article","venue":"GRURRR. Gewerblicher Rechtsschutz und Urheberrecht, Rechtsprechungs-Report/GRUR-DVD/GRUR-CD/IIC/Gewerblicher Rechtsschutz und Urheberrecht/Gewerblicher Rechtsschutz und Urheberrecht. Internationaler Teil","topic":"Law, AI, and Intellectual Property","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"Agence Nationale de la Recherche","keywords":"Complementarity (molecular biology); Intersection (aeronautics); Computer science; Geography; Cartography; Biology; Genetics","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":[0.01231944,0.0005093798,0.001596209,0.00414637,0.004502661,0.02262729,0.003062124,0.004699766,0.03694936],"category_scores_gemma":[0.04351062,0.0007933049,0.0007338371,0.00652773,0.03557493,0.04099661,0.01353836,0.008669865,0.003069936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005772907,"about_ca_system_score_gemma":0.005924396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004989329,"about_ca_topic_score_gemma":0.003637732,"domain_scores_codex":[0.9849799,0.007447362,0.0008083356,0.002279829,0.002718539,0.001766024],"domain_scores_gemma":[0.9599108,0.02589475,0.003123199,0.003637013,0.005251491,0.002182818],"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":[0.00003387959,0.00001621107,0.0007415027,0.00007249667,0.00001789137,0.00004445839,0.001267555,0.0001585226,0.00003268822,0.9822984,0.002255636,0.01306078],"study_design_scores_gemma":[0.0000131866,0.00001058724,0.0008610985,0.000156739,0.00001900712,0.0000652119,0.003333677,0.0004737453,0.00005536431,0.9849495,0.01005067,0.00001126373],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.03966362,0.01635708,0.05134419,0.1176563,0.0006177318,0.00008716912,0.0004100064,0.0001345046,0.7737294],"genre_scores_gemma":[0.9794123,0.003683663,0.004849528,0.003898949,0.0006941837,0.0001438691,0.0001315426,0.0000963044,0.007089542],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03694936,"threshold_uncertainty_score":0.1236079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07979421223829279,"score_gpt":0.3375114270199502,"score_spread":0.2577172147816574,"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."}}