{"id":"W2566529875","doi":"10.1002/2016wr019752","title":"A platform for probabilistic Multimodel and Multiproduct Streamflow Forecasting","year":2016,"lang":"en","type":"article","venue":"Water Resources Research","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Oceanic and Atmospheric Administration; Manitoba Medical Service Foundation; National Aeronautics and Space Administration","keywords":"Streamflow; Flood forecasting; Probabilistic logic; Probabilistic forecasting; Computer science; Environmental science; Consensus forecast; Calibration; Hydrological modelling; Meteorology; Econometrics; Climatology; Drainage basin; Statistics; Mathematics; Geography; Geology; Artificial intelligence","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":[0.002171356,0.0006135058,0.0004227736,0.0006991882,0.000346531,0.0007601449,0.001408659,0.0005949283,0.002706251],"category_scores_gemma":[0.004554795,0.0004082624,0.0006203242,0.000526723,0.0003178132,0.001475447,0.001278217,0.0009457087,0.0006982686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005452174,"about_ca_system_score_gemma":0.001108027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00892482,"about_ca_topic_score_gemma":0.004806844,"domain_scores_codex":[0.9993598,0.000161612,0.00004676281,0.0001431525,0.0002411252,0.00004756354],"domain_scores_gemma":[0.9982061,0.000708149,0.0001926343,0.0004197441,0.0003556249,0.0001176585],"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":[0.0004033818,0.0003758364,0.009922011,0.00006606474,0.0001460013,0.0001389521,0.0001215723,0.8414284,0.0125089,0.005107201,0.003828201,0.1259535],"study_design_scores_gemma":[0.00001459708,0.00003041468,0.0004899691,0.000002039132,0.000003263341,0.000006889019,0.000003543519,0.9963675,0.001685525,0.0007544289,0.000634179,0.000007670347],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1520549,0.00007551895,0.8176715,0.0002167656,0.00008866686,0.0003708909,0.001071311,0.0254493,0.003001061],"genre_scores_gemma":[0.5346337,0.00005546452,0.461628,0.00005716177,0.00003539256,0.000264917,0.001896242,0.0004375067,0.0009917131],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00892482,"threshold_uncertainty_score":0.01774573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0929445231133932,"score_gpt":0.3040655127789008,"score_spread":0.2111209896655076,"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."}}