{"id":"W4249802737","doi":"10.5194/hess-2018-232","title":"Quantifying projected changes in runoff variability and flow regimesof the Fraser River Basin, British Columbia","year":2018,"lang":"en","type":"preprint","venue":"","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Pacific Institute for Climate Solutions; University of Victoria; University of Northern British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Global Water Futures; University of Northern British Columbia; U.S. Department of Energy","keywords":"Environmental science; Surface runoff; Precipitation; Coupled model intercomparison project; Drainage basin; Streamflow; Snow; Structural basin; Watershed; Climate change; Hydrology (agriculture); Climatology; Climate model; Geography; Geology; Meteorology; Ecology; Oceanography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003290212,0.0003236857,0.0001651199,0.0005812302,0.0007231644,0.001101741,0.0005148204,0.0003784643,0.001665629],"category_scores_gemma":[0.0009534736,0.0001617983,0.0002388214,0.00166185,0.0002404135,0.0002826236,0.0003352948,0.0003510866,0.0002016955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01187033,"about_ca_system_score_gemma":0.008940405,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9822093,"about_ca_topic_score_gemma":0.9906304,"domain_scores_codex":[0.999788,0.00002643652,0.000008864401,0.00004353817,0.0000705419,0.00006265146],"domain_scores_gemma":[0.9995461,0.00004020807,0.00004021869,0.00001971566,0.0002919863,0.00006177199],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001570566,0.0001012957,0.7818378,0.0001076381,0.0001857981,0.0003001761,0.0003506423,0.1668737,0.003287407,0.000852943,0.01055827,0.03538736],"study_design_scores_gemma":[0.00002637944,0.00002789923,0.8690142,0.00004982363,0.00005289417,0.00003385266,0.0007439957,0.1217957,0.0009695389,0.0002153893,0.007028445,0.00004174819],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9846163,0.0002120254,0.0006231954,0.0004353583,0.000008957011,0.00002497032,0.009430709,0.0001278104,0.004520713],"genre_scores_gemma":[0.9933176,0.0002011572,0.0007289926,0.00005209221,0.000002307152,0.00001856706,0.0042916,0.00001168919,0.001376102],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01779068,"threshold_uncertainty_score":0.08612573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02038949667129204,"score_gpt":0.2329334765144832,"score_spread":0.2125439798431912,"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."}}