{"id":"W2626855999","doi":"10.1007/s11069-017-2947-7","title":"Use of remote sensing data in comprehending an extremely unusual flooding event over southwest Bangladesh","year":2017,"lang":"en","type":"article","venue":"Natural Hazards","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":38,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Flood myth; Flooding (psychology); Hydrometeorology; Natural hazard; Livelihood; Floodplain; Natural disaster; Monsoon; Water resource management; BENGAL; Geography; Environmental science; Damages; Hydrology (agriculture); Agriculture; Cartography; Geology; Meteorology; Precipitation; Bay","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":[0.0001914762,0.0001918574,0.00009373419,0.0008925778,0.0003578397,0.0004807429,0.0002157033,0.0003765201,0.0008417387],"category_scores_gemma":[0.001129204,0.0001138161,0.00008912307,0.0007282475,0.0001676612,0.0004737209,0.0002889123,0.0002001634,0.0002601862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004603785,"about_ca_system_score_gemma":0.0004072552,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03648017,"about_ca_topic_score_gemma":0.09206232,"domain_scores_codex":[0.9999189,0.00001868008,0.00001356763,0.00001389415,0.00001706075,0.00001780114],"domain_scores_gemma":[0.9995875,0.0001751001,0.00009159485,0.00002607166,0.0000770842,0.0000425943],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004122561,0.0002267597,0.8121101,0.0002330882,0.00007854855,0.00688757,0.00912708,0.01130965,0.04994996,0.0006517747,0.002849334,0.1061638],"study_design_scores_gemma":[0.00002194379,0.0001853305,0.9382605,0.00007930816,0.00007583408,0.001080337,0.02291608,0.0264982,0.004555764,0.0004811519,0.005785831,0.0000597841],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956229,0.00003951979,0.0004307414,0.0001486464,0.000004758615,0.00002418837,0.0007170028,0.00002703467,0.002985231],"genre_scores_gemma":[0.9983753,0.00007787605,0.0009111391,0.00001518598,0.000003002941,0.000008727382,0.0003211547,0.000003276541,0.0002843686],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03648017,"threshold_uncertainty_score":0.07253563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06792499904380561,"score_gpt":0.3335943122899029,"score_spread":0.2656693132460973,"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."}}