{"id":"W2916687336","doi":"10.1007/s00382-019-04676-6","title":"Development and testing of a subgrid glacier mass balance model for nesting in the Canadian Regional Climate Model","year":2019,"lang":"en","type":"article","venue":"Climate Dynamics","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Glacier; Glacier mass balance; Downscaling; Climatology; Terrain; Geology; Climate change; Elevation (ballistics); Climate model; Environmental science; Physical geography; Geomorphology; Geography; Cartography","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":[0.001026328,0.0008551906,0.0006777682,0.0005362493,0.001801502,0.001242617,0.00346292,0.0009561946,0.004501295],"category_scores_gemma":[0.003132056,0.0006687489,0.0006300579,0.0005233812,0.0005738805,0.00113395,0.000718284,0.001095053,0.0005494003],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008293163,"about_ca_system_score_gemma":0.01733972,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9465469,"about_ca_topic_score_gemma":0.9348474,"domain_scores_codex":[0.9997233,0.00006779499,0.00001500979,0.0000559556,0.00006026615,0.00007760624],"domain_scores_gemma":[0.9989645,0.0002465964,0.0000437777,0.00007431776,0.000516111,0.0001545408],"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":[0.0001020557,0.0001321846,0.01016705,0.00003602743,0.00007960111,0.00005518432,0.00008590228,0.9761457,0.0007914365,0.002935857,0.002801578,0.006667294],"study_design_scores_gemma":[0.0000667335,0.00001168835,0.001771991,0.000005508408,0.00001831598,0.00000321256,0.00003109366,0.9967428,0.0002343111,0.000215306,0.0008858274,0.0000132427],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9243647,0.0002809036,0.03348287,0.00133869,0.0002232105,0.0003722089,0.008981578,0.00300579,0.02794997],"genre_scores_gemma":[0.9610896,0.0001249601,0.03132623,0.0001576032,0.00002356262,0.0001222231,0.0034135,0.0003740884,0.003368218],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05345309,"threshold_uncertainty_score":0.1075357,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05090849913893159,"score_gpt":0.2293912591448242,"score_spread":0.1784827600058926,"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."}}