{"id":"W2066776898","doi":"10.1002/hyp.5168","title":"Impact of meteorological predictions on real‐time spring flow forecasting","year":2003,"lang":"en","type":"article","venue":"Hydrological Processes","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Environmental science; Inflow; Calibration; Meteorology; Precipitation; Hydrological modelling; Quantitative precipitation forecast; Climatology; Spring (device); Lead time; Numerical weather prediction; Statistics; Mathematics; Geology","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":[0.004249205,0.0004985347,0.0003721229,0.0002632351,0.0002736264,0.0007954866,0.0005303222,0.0006181099,0.0004652727],"category_scores_gemma":[0.02717851,0.0003167904,0.0002801196,0.0003296718,0.0003984897,0.001100041,0.0005269158,0.0007456579,0.0001375064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005848522,"about_ca_system_score_gemma":0.0007244484,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008576771,"about_ca_topic_score_gemma":0.005013618,"domain_scores_codex":[0.9979264,0.001123089,0.0001202616,0.0002493264,0.0004814508,0.00009946387],"domain_scores_gemma":[0.9756746,0.01789654,0.002279303,0.001949028,0.00195363,0.0002469279],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.001299788,0.0002179329,0.0608658,0.00006263946,0.0001297973,0.0001339763,0.0001574849,0.8785744,0.01147453,0.0004078814,0.0004247399,0.04625103],"study_design_scores_gemma":[0.00008422061,0.0004699263,0.03374506,0.00002565575,0.00005037236,0.00005714647,0.00005901309,0.9346312,0.02990898,0.0004614531,0.0004587565,0.00004827319],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9855778,0.0001329915,0.01299419,0.0001878795,0.00003790468,0.00001290426,0.0001220122,0.0002827166,0.0006516175],"genre_scores_gemma":[0.9974721,0.00003573711,0.00224762,0.00001009487,0.000006275489,0.000004609066,0.0001079261,0.00001060983,0.0001050059],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008576771,"threshold_uncertainty_score":0.0224722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02877470170656032,"score_gpt":0.2501414200191788,"score_spread":0.2213667183126184,"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."}}