{"id":"W4213066061","doi":"10.1029/2021wr030035","title":"Development of a Stepwise‐Clustered Multi‐Catchment Hydrological Model for Quantifying Interactions in Regional Climate‐Runoff Relationships","year":2022,"lang":"en","type":"article","venue":"Water Resources Research","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Environmental science; Watershed; Surface runoff; Drainage basin; Hydrology (agriculture); Precipitation; Computer science; Meteorology; Geography; Geology; Ecology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0007294276,0.0004082412,0.0004784224,0.0004572974,0.0003720155,0.0005546134,0.001725031,0.0008805371,0.001217937],"category_scores_gemma":[0.001074627,0.0003933939,0.000888603,0.0005912893,0.000316363,0.0005630575,0.0006118101,0.0006782542,0.000159893],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009296834,"about_ca_system_score_gemma":0.002013592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0347367,"about_ca_topic_score_gemma":0.02880309,"domain_scores_codex":[0.9998117,0.00006613703,0.000009676703,0.00004624728,0.00003927869,0.00002688714],"domain_scores_gemma":[0.9997014,0.0001355074,0.00003495813,0.00001961101,0.00008459276,0.0000238705],"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":[0.000006991234,0.00001115097,0.0007184891,0.000005595607,0.00001487381,0.00001217011,0.00000835569,0.9962534,0.000382097,0.0006003908,0.00007283463,0.001913663],"study_design_scores_gemma":[0.000001044455,0.00000161512,0.00007794621,3.841016e-7,0.000001299932,7.218916e-7,0.00000118122,0.9997589,0.00002888857,0.0001053366,0.00002178651,9.171607e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1678561,0.0001065967,0.8285566,0.0002186226,0.00002744689,0.0001047903,0.0004719541,0.0004330636,0.00222486],"genre_scores_gemma":[0.9208755,0.00007799999,0.07695629,0.00004096489,0.00001374783,0.0002406917,0.0003120738,0.00005764911,0.001425077],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0347367,"threshold_uncertainty_score":0.06906903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3306176823102679,"score_gpt":0.3914048336597343,"score_spread":0.06078715134946638,"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."}}