{"id":"W3121308685","doi":"10.18651/rwp2017-09","title":"Financial Vulnerability and Personal Finance Outcomes of Natural Disasters","year":2017,"lang":"en","type":"preprint","venue":"The Federal Reserve Bank of Kansas City Research Working Papers","topic":"Agricultural risk and resilience","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preparedness; Finance; Natural disaster; Vulnerability (computing); Damages; Census; Emergency management; Census tract; Quarter (Canadian coin); Business; Geography; Economics; Population; Political science; Economic growth; Demography; Meteorology; Computer security","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009767411,0.0003704,0.0003062446,0.0005699,0.0004359859,0.0009221775,0.0004064704,0.0005088445,0.007580146],"category_scores_gemma":[0.006649964,0.0000912844,0.0006093348,0.0008063206,0.0006636255,0.000789568,0.001449911,0.0009663357,0.0006945937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005625783,"about_ca_system_score_gemma":0.0003460644,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006354402,"about_ca_topic_score_gemma":0.007389459,"domain_scores_codex":[0.9995378,0.0001641249,0.0000270397,0.00006716993,0.0000640621,0.0001397126],"domain_scores_gemma":[0.9931878,0.002512646,0.002787831,0.0002198678,0.0002242567,0.00106763],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004505115,0.0003514112,0.9855325,0.00005005884,0.0002871145,0.0001457272,0.0003275772,0.002787661,0.0001314648,0.0007745287,0.00122976,0.007931896],"study_design_scores_gemma":[0.00001176931,0.0003708877,0.9955604,0.00002137424,0.00006527013,0.00004719605,0.000921568,0.001242575,0.0002175518,0.0008721878,0.0006590479,0.00001026334],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966549,0.0002196878,0.0001315917,0.0004310965,0.00001426782,0.00001187538,0.0009531833,0.000005076226,0.001578427],"genre_scores_gemma":[0.998517,0.0001105068,0.00004268956,0.00003257083,0.00001730479,0.00001170308,0.0006684231,0.000001256531,0.0005985715],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007580146,"threshold_uncertainty_score":0.02535808,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08337400544493243,"score_gpt":0.333632018071906,"score_spread":0.2502580126269736,"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."}}