{"id":"W3119893968","doi":"10.2139/ssrn.3723771","title":"Adverse Climate Incidents and Bank Loan Contracting","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Insurance and Financial Risk Management","field":"Economics, Econometrics and Finance","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Business; Loan; Adverse selection; Finance; Financial system; Actuarial science","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":[0.001734438,0.000105065,0.0002658921,0.0006903145,0.0007339152,0.00225273,0.0003711589,0.001366931,0.01266983],"category_scores_gemma":[0.0136273,0.0001794504,0.0002806115,0.0010986,0.0008438556,0.001067985,0.0009925781,0.00206333,0.0004926905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006357003,"about_ca_system_score_gemma":0.0009000868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007926084,"about_ca_topic_score_gemma":0.007717727,"domain_scores_codex":[0.9992612,0.0003146364,0.00005201753,0.00004328503,0.00008583981,0.0002429755],"domain_scores_gemma":[0.9828889,0.00755148,0.005919178,0.0004307867,0.0007610848,0.002448555],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001272127,0.001489673,0.8810436,0.000119971,0.0001520765,0.001261198,0.001860022,0.01331446,0.0003874185,0.06378131,0.008159245,0.02715888],"study_design_scores_gemma":[0.0001004418,0.0005314593,0.8480196,0.0001198836,0.0001406825,0.0007835762,0.01116875,0.0236882,0.0003524842,0.105221,0.009804002,0.00006990682],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9815808,0.000955172,0.0007405046,0.003130394,0.00007036434,0.00001462445,0.0002221285,0.000009010355,0.01327704],"genre_scores_gemma":[0.9971571,0.0005692772,0.0000474764,0.00008907116,0.0001038897,0.000003714528,0.00008056515,0.00000300795,0.001945938],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01266983,"threshold_uncertainty_score":0.0423848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01424037711080685,"score_gpt":0.2124140623799994,"score_spread":0.1981736852691926,"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."}}