{"id":"W2769009462","doi":"10.1175/jhm-d-17-0002.1","title":"Uncertainty of Hydrological Model Components in Climate Change Studies over Two Nordic Quebec Catchments","year":2017,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":66,"is_retracted":false,"has_abstract":true,"ca_institutions":"Rio Tinto (Canada); École de Technologie Supérieure; Université du Québec à Montréal","funders":"École de technologie supérieure","keywords":"Streamflow; Environmental science; Snowmelt; Climate change; Evapotranspiration; Climatology; Climate model; Hydrometeorology; Coupled model intercomparison project; Drainage basin; Representative Concentration Pathways; Snow; Hydrological modelling; Precipitation; Meteorology; Geography; Geology","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":[],"consensus_categories":[],"category_scores_codex":[0.001169774,0.0002102302,0.0007681155,0.0001804915,0.000245586,0.00001083992,0.0006883967,0.0001112106,0.0001258253],"category_scores_gemma":[0.0001227038,0.0001558446,0.0001408329,0.00007792415,0.001024128,0.000439927,0.001000199,0.0003022054,0.00003448029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001621571,"about_ca_system_score_gemma":0.000006081579,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002364081,"about_ca_topic_score_gemma":0.003335756,"domain_scores_codex":[0.9980939,0.0001748647,0.0006808272,0.0002636107,0.0003004638,0.0004863412],"domain_scores_gemma":[0.9985336,0.00008606628,0.000941401,0.0003537587,0.00002077949,0.00006436933],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005803757,0.0004326626,0.9476821,0.00003253557,0.0003178018,0.0002981182,0.001606595,0.04396806,0.002780616,0.0001941957,0.0004358355,0.001671142],"study_design_scores_gemma":[0.004285311,0.0009111014,0.9583928,0.00006096786,0.0001783386,0.00005330175,0.0001023754,0.02459639,0.0001542908,0.01031037,0.0006687468,0.0002859907],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958698,0.0002989917,0.00002029349,0.002122726,0.0003784162,0.0001716685,0.000005172637,0.000006069229,0.001126842],"genre_scores_gemma":[0.9982351,0.0008159666,0.0002068931,0.0005885115,0.00003900132,0.00001378258,0.000001262521,0.000009067206,0.00009038799],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01937168,"threshold_uncertainty_score":0.6355159,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07528952480537991,"score_gpt":0.335444483079784,"score_spread":0.2601549582744041,"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."}}