{"id":"W2313741546","doi":"10.3166/jesa.46.633-647","title":"A new data-based modelling method for identifying parsimonious nonlinear rainfall/ﬂow models","year":2012,"lang":"en","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Vineyard; Identification (biology); Surface runoff; Environmental science; Nonlinear system; Variable (mathematics); Hydrology (agriculture); Computer science; Mathematics; Geography; Engineering; Ecology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.002587759,0.0009206232,0.001352227,0.001647418,0.000610122,0.001217009,0.001253502,0.001108087,0.004095125],"category_scores_gemma":[0.009397299,0.0008224957,0.001393141,0.001302956,0.0006352197,0.001397847,0.001710513,0.002086241,0.001089376],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005318457,"about_ca_system_score_gemma":0.001291221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003778035,"about_ca_topic_score_gemma":0.004003501,"domain_scores_codex":[0.9990208,0.0004289528,0.00008507242,0.0001917851,0.0002290937,0.00004428808],"domain_scores_gemma":[0.9958983,0.003046601,0.0002706021,0.0002959878,0.0004119654,0.00007657562],"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":[0.0002109305,0.0001218613,0.001864684,0.0002705158,0.0002842885,0.0001596185,0.0002491105,0.5726981,0.007275236,0.03288291,0.001851758,0.382131],"study_design_scores_gemma":[0.00001188395,0.00001460451,0.0001322993,0.000009799312,0.00001302439,0.00002497048,0.000005559941,0.9931051,0.0004248756,0.005179617,0.001068112,0.00001003305],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001819715,0.0000374826,0.9977334,0.0000270171,0.00001188916,0.00001504315,0.0000410588,0.0001309206,0.0001834598],"genre_scores_gemma":[0.08521935,0.0001549826,0.9115702,0.00005285885,0.00006197082,0.0003588078,0.0003912607,0.0001845135,0.002006127],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004095125,"threshold_uncertainty_score":0.01369959,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08769429771371164,"score_gpt":0.3188114628157515,"score_spread":0.2311171651020398,"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."}}