{"id":"W2109957029","doi":"10.1175/jhm-d-11-0151.1","title":"Predicting the Net Basin Supply to the Great Lakes with a Hydrometeorological Model","year":2012,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":76,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact; Environment and Climate Change Canada","funders":"","keywords":"Hydrometeorology; Precipitation; Environmental science; Forcing (mathematics); Surface runoff; Snowmelt; Evaporation; Snow; Streamflow; Drainage basin; Hydrology (agriculture); Climatology; Flux (metallurgy); Structural basin; Meteorology; Atmospheric sciences; Geology; Geomorphology","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":[0.0002721377,0.0003927315,0.0002337022,0.0002177295,0.0002994547,0.0005553449,0.0005229239,0.0004643593,0.0007612725],"category_scores_gemma":[0.0007302789,0.0003249085,0.0003660481,0.0002716193,0.0002696837,0.0004105561,0.0003516196,0.0003707535,0.00009176792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001593843,"about_ca_system_score_gemma":0.001431596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1834418,"about_ca_topic_score_gemma":0.1244368,"domain_scores_codex":[0.9999268,0.00002224755,0.000003787517,0.00002146301,0.00001408725,0.00001161706],"domain_scores_gemma":[0.9997818,0.00009807826,0.00002157825,0.0000208185,0.00004433898,0.00003337861],"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":[0.00002974532,0.00001621022,0.009640166,0.000007638218,0.00001647213,0.00001910127,0.00001177509,0.9869186,0.0008223478,0.0002332415,0.0001761827,0.00210846],"study_design_scores_gemma":[0.000006514326,0.000006281852,0.001763738,6.901669e-7,0.000002609347,9.917499e-7,0.000003528521,0.9979008,0.0001651073,0.00006193153,0.00008569083,0.000002082139],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9898401,0.00004511387,0.007266404,0.0001789427,0.00001342062,0.00001637907,0.0005093438,0.000196634,0.001933674],"genre_scores_gemma":[0.9955218,0.00002105172,0.003619364,0.0000136983,0.000006046796,0.00001634539,0.0002743069,0.00001484569,0.0005126165],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1834418,"threshold_uncertainty_score":0.3647481,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01353635682699592,"score_gpt":0.2207170333685376,"score_spread":0.2071806765415417,"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."}}