{"id":"W2913066849","doi":"10.3390/rs11030252","title":"Near-Real-Time Flood Forecasting Based on Satellite Precipitation Products","year":2019,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":83,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Resources Canada","keywords":"Environmental science; Flood myth; Precipitation; Flood forecasting; Hydrograph; Meteorology; Satellite; Storm; Global Precipitation Measurement; Hydrology (agriculture); Geology; Geography","routes":{"ca_aff":false,"ca_fund":true,"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":[0.0002654899,0.000355624,0.0002159402,0.001016269,0.0001270568,0.0003992997,0.0003079415,0.0001872232,0.0004693244],"category_scores_gemma":[0.0008233567,0.0001463115,0.0002255056,0.0008750695,0.0001415774,0.0006213114,0.0002471042,0.0001807382,0.0001716594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007445943,"about_ca_system_score_gemma":0.0006889136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1076875,"about_ca_topic_score_gemma":0.1345797,"domain_scores_codex":[0.9998589,0.0000159776,0.00001011697,0.00003505154,0.00005658869,0.00002339579],"domain_scores_gemma":[0.9996843,0.0000650729,0.0000580665,0.00002965161,0.0001342737,0.00002867499],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004241103,0.0001429741,0.2247536,0.0001074848,0.0001420886,0.000222335,0.0001224603,0.6226286,0.01640888,0.0005707694,0.002476798,0.1319998],"study_design_scores_gemma":[0.00001151259,0.00003594818,0.09596393,0.000006662199,0.00002504247,0.00002209547,0.00005592424,0.9008152,0.002378742,0.0001221774,0.0005461847,0.00001660176],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.983362,0.0001626045,0.01190789,0.00007941316,0.00001472883,0.00002566902,0.001991541,0.0004551843,0.002000957],"genre_scores_gemma":[0.9925815,0.00010961,0.005245892,0.000006759762,0.000006986956,0.000008829847,0.001689255,0.000007969224,0.0003432401],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1076875,"threshold_uncertainty_score":0.2141213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01172762279172287,"score_gpt":0.2183146608008794,"score_spread":0.2065870380091565,"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."}}