{"id":"W2773911744","doi":"10.2139/ssrn.3073435","title":"What Is a New Object? Case Studies of Classification Problems and Practices at the Intersection of Law and Biotechnology.","year":2017,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Law, AI, and Intellectual Property","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Intersection (aeronautics); Object (grammar); Law; Political science; Engineering; Biotechnology; Computer science; Artificial intelligence; Biology; Transport engineering","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.02506471,0.0003687132,0.000609854,0.003491004,0.01511635,0.01535746,0.002952598,0.008644068,0.004222977],"category_scores_gemma":[0.04642751,0.0003659902,0.0008812165,0.008695912,0.0169336,0.01623251,0.006847714,0.005734676,0.0007170031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008682414,"about_ca_system_score_gemma":0.00576014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0120391,"about_ca_topic_score_gemma":0.02303937,"domain_scores_codex":[0.9703156,0.02203541,0.0009481934,0.001198261,0.003843149,0.001659458],"domain_scores_gemma":[0.9517179,0.0381697,0.003033955,0.0034899,0.002084823,0.001503733],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001938261,0.0005158167,0.01501358,0.0002791312,0.0000361202,0.005203209,0.1019026,0.001201763,0.0009829248,0.792798,0.008828436,0.07304467],"study_design_scores_gemma":[0.0001110218,0.0003038705,0.01043037,0.001469385,0.0001059317,0.00531945,0.2141909,0.00738734,0.004299125,0.415087,0.3411817,0.0001139681],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5276225,0.009011365,0.06034473,0.06369516,0.0004601315,0.001100457,0.0002841694,0.00008063515,0.3374009],"genre_scores_gemma":[0.941568,0.003434108,0.03329604,0.002185048,0.00007120516,0.000317624,0.0001620975,0.00005049586,0.01891544],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9848837,"threshold_uncertainty_score":0.1325564,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06786940553365618,"score_gpt":0.320525346763305,"score_spread":0.2526559412296488,"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."}}