{"id":"W203363839","doi":"","title":"Confusion About Causation in Insurance: Solutions for Catastrophic Losses","year":2009,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Law, Economics, and Judicial Systems","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Causation; Context (archaeology); Tort; Actuarial science; Damages; Business; Law and economics; Insurance policy; Economics; Political science; Law; Liability","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":[],"consensus_categories":[],"category_scores_codex":[0.002033116,0.0001203334,0.0003666047,0.0002614654,0.0003026678,0.00008599207,0.0001955284,0.0001158279,0.00002544442],"category_scores_gemma":[0.00009262238,0.0001639111,0.0001342583,0.0001506073,0.00004627585,0.0003420329,0.00001246941,0.0005515668,0.00007859051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001196089,"about_ca_system_score_gemma":0.0003970615,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005726032,"about_ca_topic_score_gemma":0.00253885,"domain_scores_codex":[0.9972378,0.0000191968,0.0008042312,0.0002631987,0.00003110025,0.001644491],"domain_scores_gemma":[0.9992392,0.00002917182,0.0004651637,0.0001548655,0.00004508621,0.00006652756],"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":[0.00004244677,0.00008447685,0.02050915,0.000005945752,0.00002974647,7.004552e-7,0.0001668266,0.0003742147,0.00004599876,0.9740788,0.000176228,0.00448541],"study_design_scores_gemma":[0.001370492,0.0003225436,0.04813776,0.00002618056,0.000004502791,0.00005146609,0.0001975745,0.0006987092,0.00001159346,0.9436974,0.005258702,0.0002231013],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9408935,0.01499647,0.03361293,0.002351225,0.001102835,0.0005744996,0.0001516767,0.00003538482,0.00628143],"genre_scores_gemma":[0.9938011,0.005021585,0.00005111467,0.0001656889,0.0005961079,0.00001527238,0.00002462086,0.000016458,0.0003080965],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05290751,"threshold_uncertainty_score":0.66841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02178221319545287,"score_gpt":0.2278605222714237,"score_spread":0.2060783090759708,"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."}}