{"id":"W2600748549","doi":"10.1002/hyp.11185","title":"Hyd<scp>R</scp>un: <scp>A MATLAB</scp> toolbox for rainfall–runoff analysis","year":2017,"lang":"en","type":"article","venue":"Hydrological Processes","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":88,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Hydrograph; Streamflow; Surface runoff; Toolbox; Computer science; Runoff model; Hydrology (agriculture); Base flow; Baseflow; Watershed; Environmental science; Precipitation; Meteorology; Drainage basin; Geology; Machine learning; Ecology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007385266,0.0004495955,0.000684704,0.0001092838,0.001957302,0.0002435156,0.001385065,0.0003156611,0.0003863841],"category_scores_gemma":[0.004147074,0.0003333493,0.0002805918,0.0004419076,0.001131711,0.0005975069,0.0009167464,0.0002562207,0.0007885773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004879888,"about_ca_system_score_gemma":0.00001198271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007587038,"about_ca_topic_score_gemma":0.0001590859,"domain_scores_codex":[0.9969949,0.00007889036,0.0004417446,0.001055019,0.0004038998,0.001025603],"domain_scores_gemma":[0.9975778,0.0009974474,0.0003917363,0.0007868654,0.00004245798,0.0002036502],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007952873,0.001278049,0.843648,0.0004714389,0.003213696,0.000217276,0.002829143,0.02212336,0.001257935,0.001202098,0.1204336,0.003245844],"study_design_scores_gemma":[0.002284862,0.001088784,0.3118637,0.00002392278,0.002439694,0.00001461872,0.0005704592,0.007629531,0.005322304,0.04279358,0.6255505,0.000418091],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8869428,0.0003448278,0.003720658,0.001825722,0.0001678912,0.0006932812,0.00003035179,0.000262531,0.1060119],"genre_scores_gemma":[0.9848394,0.000254551,0.00111743,0.002114721,0.0001367358,0.0003392525,0.00004256273,0.0000245784,0.01113079],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5317844,"threshold_uncertainty_score":0.9999894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02147480740348589,"score_gpt":0.2527268052947506,"score_spread":0.2312519978912647,"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."}}