{"id":"W4382060397","doi":"10.5194/egusphere-2023-1367","title":"Uncertainties originating from GCM downscaling and bias correction with application to the MIS-11c Greenland Ice Sheet","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; Alliance de recherche numérique du Canada; Universität Bremen; Deutsche Forschungsgemeinschaft","keywords":"Greenland ice sheet; Climatology; Downscaling; Interglacial; Ice-sheet model; Ice sheet; Future sea level; Climate model; Forcing (mathematics); Marine isotope stage; Environmental science; Geology; General Circulation Model; Climate change; Sea ice; Glacial period; Cryosphere; Oceanography; Ice stream; Geomorphology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.00370903,0.0008330481,0.0004396562,0.001057804,0.0007030607,0.0009865006,0.0007238528,0.0005990101,0.0006753136],"category_scores_gemma":[0.009341806,0.000339504,0.0008273062,0.001491913,0.0004020185,0.000649001,0.0006345411,0.0005306066,0.0001586203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001163164,"about_ca_system_score_gemma":0.001663771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05723809,"about_ca_topic_score_gemma":0.06213333,"domain_scores_codex":[0.9990723,0.0002859728,0.00009994475,0.0002602993,0.0002310242,0.00005043163],"domain_scores_gemma":[0.9972152,0.001203684,0.0003112841,0.0005317549,0.00068739,0.00005065823],"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":[0.0004258527,0.000124833,0.2884261,0.0003000806,0.001066658,0.0003383614,0.0005149185,0.578582,0.0171303,0.001832628,0.002591028,0.1086672],"study_design_scores_gemma":[0.0000978289,0.00006845312,0.2654456,0.0001301323,0.0002636171,0.00007850001,0.0002271913,0.7122685,0.01503845,0.0012058,0.005075367,0.0001005844],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9704869,0.0005747912,0.02243571,0.0003464406,0.0001720152,0.00006322139,0.002398554,0.0007270818,0.002795351],"genre_scores_gemma":[0.9841998,0.00009596437,0.01421572,0.00008184426,0.00002023884,0.00002957731,0.001046793,0.0001281352,0.0001818449],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05723809,"threshold_uncertainty_score":0.1138099,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04116591644880942,"score_gpt":0.2422686624272638,"score_spread":0.2011027459784543,"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."}}