{"id":"W3111092183","doi":"10.3390/jrfm13120320","title":"Natural Disasters and Economic Growth: A Semiparametric Smooth Coefficient Model Approach","year":2020,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Agricultural risk and resilience","field":"Agricultural and Biological Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Natural disaster; Econometrics; Panel data; Economics; Investment (military); Parametric statistics; Curse; Semiparametric model; Function (biology); Semiparametric regression; Nonparametric statistics; Regression analysis; Natural (archaeology); Statistics; Mathematics; Geography; Meteorology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.002845837,0.0008737101,0.001442215,0.001194258,0.0003147016,0.001896996,0.001302494,0.001550534,0.00385533],"category_scores_gemma":[0.01066668,0.0008330172,0.001518405,0.001061296,0.001310498,0.00162412,0.001662273,0.002129662,0.0006492513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007388266,"about_ca_system_score_gemma":0.000856351,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008217552,"about_ca_topic_score_gemma":0.004942946,"domain_scores_codex":[0.9990166,0.0005481261,0.00003378312,0.0001573066,0.00008152272,0.0001624835],"domain_scores_gemma":[0.9924151,0.005410937,0.0009798091,0.0005187393,0.0004302219,0.0002451341],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001042355,0.00006291281,0.01073916,0.0001093025,0.0002783067,0.0004507577,0.0002011126,0.8663757,0.0009817026,0.1099456,0.00272465,0.008026564],"study_design_scores_gemma":[0.00001864337,0.00004038809,0.00268163,0.00002002691,0.00005981361,0.00005850403,0.00006674314,0.9478789,0.0001366799,0.04793128,0.001076342,0.00003105138],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2925339,0.001951066,0.6905037,0.003443613,0.0001286074,0.0001062358,0.002128786,0.0004790307,0.008724984],"genre_scores_gemma":[0.9751471,0.001420097,0.01408165,0.000181264,0.0001169708,0.0001228788,0.0008927869,0.00008732345,0.007950015],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008217552,"threshold_uncertainty_score":0.01633942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0085426406741948,"score_gpt":0.1807191587352109,"score_spread":0.1721765180610161,"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."}}