{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","sts","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","sts","open_science","research_integrity","insufficient_payload"],"category_scores_codex":[0.01840503,0.0107102,0.009455588,0.00466496,0.007249545,0.01211778,0.02019699,0.007988761,0.004551474],"category_scores_gemma":[0.01519079,0.009249128,0.004947924,0.01624318,0.005524288,0.0137252,0.01003136,0.01794868,0.00332941],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.008311909,"about_ca_system_score_gemma":0.0072724,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01191313,"about_ca_topic_score_gemma":0.008439827,"domain_scores_codex":[0.9381111,0.008287496,0.01537095,0.01552917,0.01158312,0.01111811],"domain_scores_gemma":[0.9507003,0.01074503,0.009308193,0.01310938,0.008214298,0.007922735],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.007111629,0.006819024,0.01599695,0.002016634,0.03390667,0.005167059,0.01705116,0.0003933388,0.0138957,0.04438246,0.4931962,0.3600632],"study_design_scores_gemma":[0.01197715,0.00354341,0.003050299,0.002016964,0.004669904,0.004313832,0.001767841,0.01795298,0.02483975,0.01498475,0.898518,0.01236507],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07193679,0.08213725,0.4235586,0.1563479,0.05118356,0.03815252,0.003259677,0.02720646,0.1462173],"genre_scores_gemma":[0.6651413,0.02434487,0.07779332,0.0459487,0.02195703,0.01024683,0.008232968,0.007304971,0.13903],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5932046,"threshold_uncertainty_score":0.9983554,"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."}}