{"id":"W4320340148","doi":"10.30897/ijegeo.1073697","title":"Application of Remote Sensing and Geographical Information System (GIS) in Flood Vulnerability Mapping: A Scenario of Akure South, Nigeria","year":2023,"lang":"en","type":"article","venue":"International Journal of Environment and Geoinformatics","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Toronto","keywords":"Flood myth; Vulnerability (computing); Remote sensing; Geographic information system; Flooding (psychology); Geography; Vulnerability assessment; Cartography; Shuttle Radar Topography Mission; Environmental science; Hydrology (agriculture); Environmental resource management; Computer science; Digital elevation model; Geology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0003964414,0.0002311002,0.000131802,0.0007860077,0.0005435266,0.0006745964,0.000173634,0.0003884868,0.0006777863],"category_scores_gemma":[0.0006059275,0.0001870231,0.0001249802,0.0009456816,0.0004076648,0.000617715,0.0006589876,0.0001872239,0.00006053693],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001003308,"about_ca_system_score_gemma":0.0008555725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01946056,"about_ca_topic_score_gemma":0.03399561,"domain_scores_codex":[0.9997436,0.0001337005,0.00001386056,0.00002175935,0.00003195332,0.0000551524],"domain_scores_gemma":[0.9998034,0.00008414563,0.0000431474,0.00001044211,0.00002820373,0.00003066719],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006366913,0.0005083735,0.7635651,0.0004906019,0.00010147,0.03203239,0.009491597,0.06711264,0.01298939,0.0125729,0.002591207,0.09790773],"study_design_scores_gemma":[0.00006789654,0.0007612185,0.6815046,0.0005076264,0.0002038481,0.005997154,0.08088988,0.202747,0.007949713,0.007890387,0.0113604,0.0001201682],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959239,0.0001291,0.0009258672,0.0002267495,0.000005845112,0.00002946358,0.00009075307,0.000008906139,0.002659505],"genre_scores_gemma":[0.9984785,0.0001636306,0.001016681,0.000007299058,0.000001069641,0.00001004535,0.00003501577,8.974258e-7,0.0002868005],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01946056,"threshold_uncertainty_score":0.03869456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006700946542246534,"score_gpt":0.216097225496109,"score_spread":0.2093962789538625,"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."}}