{"id":"W4392273918","doi":"","title":"Statistical contributions to hydrometeorological forecasting from ensemble methods","year":2017,"lang":"fr","type":"preprint","venue":"","topic":"Hydrological Forecasting Using AI","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Hydrometeorology; Computer science; Statistics; Meteorology; Geography; Mathematics; Precipitation","routes":{"ca_aff":false,"ca_fund":false,"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":[0.003676252,0.0009341171,0.0008526715,0.001348758,0.0004581364,0.001647421,0.0006962005,0.0006876535,0.001152963],"category_scores_gemma":[0.01374391,0.0004392572,0.0008250787,0.001381603,0.0004317513,0.001590746,0.001164473,0.001428006,0.0003249277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005855651,"about_ca_system_score_gemma":0.001034498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009388133,"about_ca_topic_score_gemma":0.01005375,"domain_scores_codex":[0.9989525,0.0003997212,0.00007108117,0.0001495234,0.0003616732,0.00006550315],"domain_scores_gemma":[0.9929199,0.005085436,0.0002935769,0.0005252825,0.001036557,0.0001394008],"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":[0.0001116767,0.00004091436,0.00815055,0.0001010281,0.0002450251,0.00007261804,0.0001285589,0.7554065,0.002502142,0.01363038,0.001774249,0.2178363],"study_design_scores_gemma":[0.000003355298,0.00001416566,0.0009699839,0.00001462798,0.00002064689,0.0000135758,0.000007898449,0.9921669,0.0005087497,0.005134642,0.001136177,0.000009354208],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05089256,0.00324177,0.9399834,0.001136578,0.0004039482,0.00002934012,0.0002505561,0.0006005637,0.003461248],"genre_scores_gemma":[0.7446003,0.005082906,0.2427024,0.0003845734,0.001532481,0.0001029526,0.0008007513,0.0003181707,0.004475317],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009388133,"threshold_uncertainty_score":0.01944208,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08975355993030498,"score_gpt":0.3850740644005028,"score_spread":0.2953205044701978,"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."}}