{"id":"W2923370425","doi":"","title":"The Techno-Neutrality Solution to Navigating Insurance Coverage for Cyber Losses","year":2018,"lang":"en","type":"article","venue":"","topic":"Law, AI, and Intellectual Property","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Business; Liability insurance; Product (mathematics); Actuarial science; Insurance policy; Business interruption insurance; Casualty insurance; General insurance; Liability; Finance; Income protection insurance","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":[0.01239026,0.0007145467,0.0005159461,0.002041956,0.00476343,0.01460609,0.002720946,0.01138075,0.006526734],"category_scores_gemma":[0.02110559,0.000704364,0.001279362,0.0008737743,0.03113546,0.0227225,0.009005718,0.01186908,0.001366413],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00639671,"about_ca_system_score_gemma":0.009083587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002250925,"about_ca_topic_score_gemma":0.001614348,"domain_scores_codex":[0.9886627,0.004570056,0.0005350156,0.001473257,0.003761705,0.0009972708],"domain_scores_gemma":[0.9909224,0.004733132,0.001113262,0.001753355,0.001102979,0.0003749543],"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":[0.000002872302,0.000006273864,0.00006849703,0.000008806108,0.000002045164,0.00003509102,0.0003552253,0.0003513827,0.0001149206,0.9967174,0.0004453238,0.001892117],"study_design_scores_gemma":[0.00001336051,0.00003452872,0.0001062605,0.00008765437,0.00001151924,0.0001345549,0.0006398975,0.002685443,0.000606476,0.9660244,0.02963184,0.00002415104],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.04210238,0.001752884,0.4147946,0.1202634,0.001129136,0.0002626533,0.00009628746,0.0004894565,0.4191092],"genre_scores_gemma":[0.9142378,0.00111841,0.04569594,0.013743,0.0007443208,0.0003713685,0.00004443494,0.0001624386,0.02388229],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01460609,"threshold_uncertainty_score":0.06552678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02887563404556288,"score_gpt":0.2821067867867642,"score_spread":0.2532311527412013,"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."}}