{"id":"W4387873138","doi":"10.1016/j.nhres.2023.10.006","title":"Extreme weather events (EWEs)-Related health complications in Bangladesh: A gender-based analysis on the 2017 catastrophic floods","year":2023,"lang":"en","type":"article","venue":"Natural Hazards Research","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"University of Dhaka","keywords":"Sanitation; Flood myth; Extreme weather; Environmental health; Vulnerability (computing); Reproductive health; Socioeconomics; Geography; Waterborne diseases; Natural disaster; Medicine; Water resource management; Population; Climate change; Environmental 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00277571,0.0001630252,0.0002100281,0.000631752,0.0005549301,0.00006050234,0.0007965378,0.00007167264,0.001154403],"category_scores_gemma":[0.00007601958,0.0001113702,0.0001394211,0.005060449,0.0001935059,0.00009936127,0.0003872658,0.0008246144,0.00207242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006307205,"about_ca_system_score_gemma":0.00007397069,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003097736,"about_ca_topic_score_gemma":0.003214857,"domain_scores_codex":[0.9962014,0.0006818872,0.0002953934,0.0005391081,0.001496251,0.00078597],"domain_scores_gemma":[0.9987631,0.0002471052,0.00006877647,0.0007609745,0.00002748726,0.0001325715],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0002610776,0.002059118,0.3519759,0.0001048666,0.001272951,0.0001461161,0.003072533,0.114222,0.00342604,0.007230898,0.410973,0.1052556],"study_design_scores_gemma":[0.0004800738,0.00009599135,0.852111,0.00002072329,0.00002343367,3.864965e-7,0.0002563343,0.1408094,0.00003879173,0.0008183483,0.005201153,0.0001442767],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9546985,0.0002354084,0.0001123644,0.03323158,0.0001513188,0.001553877,0.00005909991,0.0001403235,0.009817521],"genre_scores_gemma":[0.9957519,0.0001062237,0.0001882345,0.0002834962,0.00001818333,0.0001805681,0.0002091049,0.00001790431,0.003244452],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5001351,"threshold_uncertainty_score":0.9997587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1238549240342948,"score_gpt":0.3994961420825311,"score_spread":0.2756412180482363,"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."}}