{"id":"W4206559285","doi":"10.1139/er-2021-0043","title":"Modelling river flow in cold and ungauged regions: a review of the purposes, methods, and challenges","year":2022,"lang":"en","type":"review","venue":"Environmental Reviews","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; Alberta Environment and Protected Areas","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Replicate; Watershed; Calibration; Environmental science; Computer science; Hydrological modelling; Process (computing); Streamflow; Flooding (psychology); Climate change; Empirical modelling; Hydrology (agriculture); Drainage basin; Machine learning; Climatology; Geography; Ecology; Statistics; Geology; Cartography; Simulation","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.001950743,0.001529206,0.002001493,0.002373775,0.0003042723,0.002053934,0.001973964,0.001410353,0.001270446],"category_scores_gemma":[0.002254482,0.0008106071,0.001697888,0.004590485,0.0008036772,0.003647217,0.0009174362,0.001531348,0.000889323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007846932,"about_ca_system_score_gemma":0.001806185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00696437,"about_ca_topic_score_gemma":0.005116981,"domain_scores_codex":[0.9993901,0.0001567623,0.0001134162,0.000149463,0.0001587148,0.00003147405],"domain_scores_gemma":[0.9988775,0.000714242,0.000115152,0.00003817808,0.0002170504,0.00003794255],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004852988,0.0001433312,0.002462926,0.02804554,0.0004369133,0.0002076668,0.0003642669,0.05949435,0.002180993,0.02493591,0.01724593,0.8644337],"study_design_scores_gemma":[0.00003953805,0.0003117707,0.005286212,0.01802178,0.000871123,0.0008445292,0.0006370723,0.08689132,0.00248828,0.04082147,0.8434448,0.0003421707],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00121672,0.9699374,0.02546794,0.0008583126,0.000329222,0.00003799597,0.0001591214,0.0001200102,0.00187327],"genre_scores_gemma":[0.004696586,0.9843816,0.009780753,0.0001542766,0.00035518,0.00004260748,0.0001685785,0.00002271246,0.0003977135],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.00696437,"threshold_uncertainty_score":0.01384765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1090422818115179,"score_gpt":0.3156914599723333,"score_spread":0.2066491781608153,"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."}}