{"id":"W2977564104","doi":"10.5539/enrr.v9n3p101","title":"Mortality Due to Meteorological Disasters in Mexico during 2000-2015","year":2019,"lang":"en","type":"article","venue":"Environment and Natural Resources Research","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Vulnerability (computing); Natural disaster; Extreme weather; Geography; Demography; Environmental health; Population; Medicine; Climate change; Biology; Meteorology; Computer security; Ecology; Sociology; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0002526722,0.00020744,0.0001392582,0.0007844024,0.0003267001,0.0002819327,0.0001893074,0.000154738,0.0008522535],"category_scores_gemma":[0.000609102,0.00008409694,0.0002581009,0.0005603757,0.0001135374,0.0002121625,0.0004491775,0.0002224178,0.00007797766],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007909216,"about_ca_system_score_gemma":0.0004516412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04147523,"about_ca_topic_score_gemma":0.05740714,"domain_scores_codex":[0.9998966,0.00001325734,0.0000137799,0.00002372757,0.00001912873,0.00003348135],"domain_scores_gemma":[0.9997726,0.00001733501,0.0001392536,0.000007721086,0.00004073994,0.00002239175],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001202003,0.00002483132,0.9875906,0.0001080588,0.00009299148,0.0001498409,0.0004771287,0.0003534306,0.0002669847,0.0001194269,0.002715426,0.007981087],"study_design_scores_gemma":[0.000002893054,0.00003001914,0.9960093,0.00003243253,0.00002568775,0.00009664954,0.0005923578,0.0001091732,0.00009586048,0.00002001994,0.002982273,0.000003288885],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9879057,0.001000996,0.0001501043,0.0003066473,0.00004558296,0.00001907654,0.00862363,0.00001931129,0.00192889],"genre_scores_gemma":[0.9891834,0.001692863,0.0001607408,0.00005639153,0.00005231664,0.00003395832,0.00793096,0.000003252569,0.0008859945],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04147523,"threshold_uncertainty_score":0.08246768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0656227396708347,"score_gpt":0.3611878289551603,"score_spread":0.2955650892843256,"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."}}