{"id":"W4243348841","doi":"10.5194/hess-2020-613","title":"The Spatial Extent of Hydrological and Landscape Changes across the Mountains andPrairies of Canada in the Mackenzie and Nelson River Basins Based on Data from aWarm Season Time Window","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; Simon Fraser University; Environment and Climate Change Canada","funders":"","keywords":"Streamflow; Climatology; Climate change; Physical geography; Structural basin; Normalized Difference Vegetation Index; Environmental science; North Atlantic oscillation; Vegetation (pathology); Snow; Drainage basin; Geography; Geology; Meteorology; Oceanography; Cartography","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":[0.0001745866,0.0001315199,0.0001632971,0.001348519,0.0009244323,0.0007087725,0.0004254745,0.000135941,0.0009597597],"category_scores_gemma":[0.0005913148,0.0001004529,0.0002120018,0.00231212,0.0002897553,0.0002019628,0.0005023997,0.0001969045,0.0001067338],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00620447,"about_ca_system_score_gemma":0.005180757,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9776898,"about_ca_topic_score_gemma":0.9920285,"domain_scores_codex":[0.9998197,0.000008950899,0.00001232056,0.00004908073,0.00005467144,0.00005534402],"domain_scores_gemma":[0.9993916,0.00004340568,0.0001146048,0.00001996424,0.0002856566,0.0001447745],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004360241,0.00001123328,0.993026,0.00001661075,0.00003267383,0.00004429615,0.0004786238,0.0001666692,0.0006472069,0.00006149407,0.0005734625,0.004898124],"study_design_scores_gemma":[8.827689e-7,0.000002238953,0.9989424,0.000005029965,0.000005588324,0.00001003684,0.0003963364,0.0001854344,0.00004780232,0.000003654184,0.0003984361,0.000002132024],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954736,0.0001239662,0.00005253922,0.00003383557,0.000001584618,0.00001023677,0.003481353,0.000006959376,0.0008159196],"genre_scores_gemma":[0.9958453,0.0001243582,0.0001791788,0.00001268751,0.000001531664,0.00001339986,0.003151743,0.000002887165,0.0006689286],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0223102,"threshold_uncertainty_score":0.04501683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01821900012038192,"score_gpt":0.2377099194726281,"score_spread":0.2194909193522462,"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."}}