{"id":"W4210521340","doi":"10.5194/tc-2022-5","title":"Validation of Pan-Arctic Soil Temperatures in Modern Reanalysis and Data Assimilation Systems","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Environmental science; Data assimilation; Snow; Arctic; Climatology; Mean squared error; Homogeneous; The arctic; Growing season; Atmospheric sciences; Meteorology; Geography; Statistics; Mathematics; Geology; Ecology","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":[0.00413656,0.0005976617,0.0003821287,0.0005716414,0.0005199587,0.0009071956,0.0005159328,0.000460722,0.0003861252],"category_scores_gemma":[0.004460496,0.000253775,0.0005379528,0.0006522204,0.0002394717,0.001064268,0.0006301149,0.0004272244,0.0002765194],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000513355,"about_ca_system_score_gemma":0.0005912136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01228617,"about_ca_topic_score_gemma":0.01560067,"domain_scores_codex":[0.9985031,0.0004577914,0.0001587843,0.0003650279,0.0004318321,0.0000835399],"domain_scores_gemma":[0.9971231,0.0004271339,0.0003529782,0.000539525,0.001469167,0.00008798605],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000755611,0.0004581677,0.5888751,0.0002392509,0.001714688,0.0001662019,0.0005223866,0.2254894,0.04336542,0.0009730709,0.003581661,0.1338591],"study_design_scores_gemma":[0.0001270842,0.0003402098,0.4981291,0.0001108453,0.0002502051,0.0001077658,0.0001964845,0.4579065,0.03484751,0.0005879069,0.007294517,0.0001018526],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9768982,0.0002488948,0.0176122,0.00007658896,0.00009260399,0.00004172612,0.002631247,0.0006394851,0.001759207],"genre_scores_gemma":[0.9747873,0.0000891995,0.02044966,0.00004196623,0.00003342762,0.00004329603,0.004283269,0.00006855567,0.0002033026],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01228617,"threshold_uncertainty_score":0.02442926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09331679022803951,"score_gpt":0.2971841055857821,"score_spread":0.2038673153577426,"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."}}