{"id":"W4248474914","doi":"10.1007/978-3-642-40457-3_6-2","title":"Verification of Medium- to Long-Range Hydrological Forecasts","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; Hydro-Québec","funders":"","keywords":"Probabilistic logic; Computer science; Probabilistic forecasting; Hydropower; Range (aeronautics); Monte Carlo method; Process (computing); Operations research; Environmental science; Artificial intelligence; Engineering; Statistics; Mathematics","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":[0.003238017,0.000418631,0.0002874761,0.0004658578,0.0004048489,0.002035649,0.001409249,0.0008061934,0.008573456],"category_scores_gemma":[0.009558474,0.0002830237,0.0003442529,0.0004204277,0.0005242052,0.002348127,0.001247441,0.001054961,0.002342697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000836323,"about_ca_system_score_gemma":0.00165608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00753351,"about_ca_topic_score_gemma":0.007475739,"domain_scores_codex":[0.9989777,0.0002123657,0.00005764329,0.0001741937,0.0005008917,0.00007729024],"domain_scores_gemma":[0.9954907,0.002004066,0.000177908,0.0009880008,0.001177609,0.0001617978],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006904191,0.0002458256,0.01682482,0.0002340477,0.0001214719,0.0004255176,0.0002870822,0.2775879,0.05432955,0.02885234,0.03252013,0.5878808],"study_design_scores_gemma":[0.00006169894,0.00007235889,0.005854863,0.00007693475,0.00002198188,0.0001201864,0.0001390033,0.9066652,0.04269401,0.02233939,0.02190852,0.00004584289],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1806646,0.00110096,0.7345865,0.002841687,0.00175897,0.0001751524,0.005073763,0.008839888,0.06495843],"genre_scores_gemma":[0.8164275,0.00046222,0.1633227,0.0002081413,0.0002580663,0.00007230158,0.005529964,0.0008311927,0.0128879],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008573456,"threshold_uncertainty_score":0.02868104,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02373349276120955,"score_gpt":0.2289253344721898,"score_spread":0.2051918417109802,"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."}}