{"id":"W2986218094","doi":"10.2166/wcc.2019.321","title":"Flood prediction based on weather parameters using deep learning","year":2019,"lang":"en","type":"article","venue":"Journal of Water and Climate Change","topic":"Hydrological Forecasting Using AI","field":"Environmental Science","cited_by":160,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Flood myth; Support vector machine; Artificial intelligence; Machine learning; Artificial neural network; Flood forecasting; Computer science; Deep learning; Meteorology; Internet of Things; Environmental science; Geography","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":[],"consensus_categories":[],"category_scores_codex":[0.0003870575,0.00008223252,0.0001243819,0.00003936695,0.00007501792,0.00002912472,0.00005778831,0.00005031131,0.0006166151],"category_scores_gemma":[0.000009821432,0.00004874256,0.0000475934,0.0000400409,0.0000357778,0.0001502243,0.000041887,0.0001675705,0.0000772365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005554636,"about_ca_system_score_gemma":7.123958e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001219111,"about_ca_topic_score_gemma":0.000001143564,"domain_scores_codex":[0.9992799,0.00005622046,0.000160077,0.0001083357,0.0001875425,0.0002079682],"domain_scores_gemma":[0.9997657,0.00002062525,0.00008619449,0.00005592771,0.00000583236,0.0000657354],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000279739,0.0001514563,0.7295238,0.00004193265,0.00001936866,0.00004679184,0.002618144,0.1965078,0.05958935,0.000002824236,0.0000126363,0.01120617],"study_design_scores_gemma":[0.002392981,0.003972107,0.09324662,0.0003901224,0.0001306009,0.0002645428,0.0002469292,0.8863796,0.00970937,0.0002203509,0.002625511,0.0004212874],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99857,0.00001211652,0.00007412544,0.0001169719,0.000156846,0.0000632291,0.000001140014,0.00001074572,0.0009948134],"genre_scores_gemma":[0.9990749,0.00001985287,0.000539757,0.0002844806,0.00005016279,7.531411e-7,0.000001354311,0.000009986959,0.00001869637],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6898717,"threshold_uncertainty_score":0.6751503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0356374776589438,"score_gpt":0.2342438468991091,"score_spread":0.1986063692401653,"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."}}