{"id":"W2981799541","doi":"10.1080/07011784.2019.1671235","title":"Towards a climate-driven simulation of coupled surface-subsurface hydrology at the continental scale: a Canadian example","year":2019,"lang":"en","type":"article","venue":"Canadian Water Resources Journal / Revue canadienne des ressources hydriques","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nuclear Waste Management Organization; University of Toronto; University of Waterloo","funders":"","keywords":"Hydrology (agriculture); Groundwater; Water cycle; Streamflow; Surface water; Water resources; Groundwater flow; Permafrost; Structural basin; Geology; Environmental science; Groundwater model; Hydrogeology; Bedrock; Scale (ratio); Subsurface flow; Water balance; Drainage basin; Aquifer; Geomorphology; Geography; Oceanography","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002746455,0.0005587504,0.0003143972,0.0004796462,0.001266833,0.001169031,0.001193209,0.0008503773,0.00177965],"category_scores_gemma":[0.0008636251,0.0003220663,0.0006009414,0.0009001276,0.0008100217,0.0004107452,0.0007574261,0.0006950088,0.0001171841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007134009,"about_ca_system_score_gemma":0.01054845,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9562068,"about_ca_topic_score_gemma":0.9395843,"domain_scores_codex":[0.9999051,0.00001293015,0.000003222504,0.0000172255,0.00003360793,0.00002791153],"domain_scores_gemma":[0.999795,0.00003954719,0.00001130672,0.00001420319,0.00009792049,0.00004193053],"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":[0.00003821959,0.0000336908,0.004990697,0.00002159477,0.00001497415,0.00007414553,0.00005632674,0.9863411,0.001282424,0.003397056,0.0006300146,0.003119824],"study_design_scores_gemma":[0.00002405682,0.000007314886,0.001535996,0.000002817865,0.000005851361,0.000004562437,0.00003465427,0.9969088,0.000237423,0.0003258373,0.0009050838,0.000007577108],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9292784,0.0002972599,0.03897665,0.001022974,0.00006888313,0.0001708927,0.002580029,0.0006193714,0.02698557],"genre_scores_gemma":[0.9653251,0.0002803594,0.0299411,0.0000976213,0.000009944883,0.00005022819,0.000844428,0.00006013052,0.003391124],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0437932,"threshold_uncertainty_score":0.08810216,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02207901716851794,"score_gpt":0.209413205227431,"score_spread":0.187334188058913,"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."}}