{"id":"W3172304935","doi":"","title":"Assessment of Large-Scale Reanalysis Forcing on Winter Simulations in the Boreal Forest Using the Canadian Land Surface Scheme","year":2018,"lang":"en","type":"article","venue":"EGU General Assembly Conference Abstracts","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Forcing (mathematics); Taiga; Climatology; Environmental science; Boreal; Scale (ratio); Meteorology; Atmospheric sciences; Geography; Geology; Forestry; Cartography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004807238,0.0001208712,0.0001556333,0.00003770215,0.0005459646,0.0001196099,0.0002679302,0.00005186758,0.0002225414],"category_scores_gemma":[0.00004011559,0.00007084617,0.00005415816,0.00034604,0.00008217915,0.0001262668,0.00001283057,0.0001586472,0.000007470273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002363299,"about_ca_system_score_gemma":0.0002617126,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.4283531,"about_ca_topic_score_gemma":0.9881908,"domain_scores_codex":[0.9988434,0.00006829661,0.0002778308,0.0001886217,0.0002876403,0.0003342612],"domain_scores_gemma":[0.9991945,0.0002014693,0.0001214548,0.0002680062,0.0001446819,0.00006988688],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000003046837,0.00001314364,0.8190354,0.000001868853,0.00001893692,0.000001957573,0.0004699596,0.1798509,0.00006691864,0.0001939696,0.0001278618,0.0002160407],"study_design_scores_gemma":[0.00009180421,0.00004034938,0.7148604,0.00001291502,0.0000156721,7.11304e-7,0.0005337531,0.2836529,0.00002552763,0.00008786748,0.0006111317,0.00006696985],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9895787,0.00002192717,0.0002034444,0.001256719,0.0001119069,0.0001603415,0.00008091664,0.000005509221,0.008580575],"genre_scores_gemma":[0.9972751,0.000007014944,0.001919524,0.0004816163,0.0001490676,8.234732e-7,0.00009650919,0.000003030482,0.00006738566],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5598377,"threshold_uncertainty_score":0.5754535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04868137847565768,"score_gpt":0.3002562414729469,"score_spread":0.2515748629972893,"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."}}