{"id":"W3194587145","doi":"","title":"On resorting to a meteorological post-processor to improve ensemble hydrological forecasts","year":2019,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Computer science; Meteorology; Weather forecasting; Climatology; Environmental science; Geology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006713175,0.0008138468,0.0006854016,0.0004087322,0.000521867,0.001393016,0.0006954916,0.0008694287,0.0129626],"category_scores_gemma":[0.005299989,0.0003483293,0.0005295007,0.0006465449,0.0002539384,0.001955082,0.0007287047,0.001565065,0.002888764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001774185,"about_ca_system_score_gemma":0.0008797956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007990013,"about_ca_topic_score_gemma":0.01551043,"domain_scores_codex":[0.9998241,0.00003537441,0.00001711747,0.00004319268,0.00005084214,0.00002934729],"domain_scores_gemma":[0.9985702,0.0005412402,0.00005046049,0.0003342952,0.0004391542,0.00006464208],"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":[0.001276794,0.0004273247,0.005779148,0.0001951404,0.0002783427,0.0002092281,0.0001799858,0.1943157,0.08758538,0.003806879,0.01185746,0.6940887],"study_design_scores_gemma":[0.00009859375,0.000157629,0.003308811,0.00001679419,0.00009041917,0.00003519756,0.00005352644,0.9602317,0.02709414,0.002136518,0.006754056,0.00002264853],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.174404,0.0003855971,0.8028274,0.001104697,0.001305809,0.0002069996,0.001026584,0.01075949,0.007979326],"genre_scores_gemma":[0.4543211,0.0003745645,0.5308275,0.0006812882,0.000617418,0.000149018,0.001859005,0.0008760261,0.01029397],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0129626,"threshold_uncertainty_score":0.04336423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01571944322410208,"score_gpt":0.220584954046873,"score_spread":0.2048655108227709,"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."}}