{"id":"W2611880342","doi":"","title":"Extended-Range High-Resolution Dynamical Downscaling over a Continental-Scale Domain","year":2014,"lang":"en","type":"article","venue":"2014 AGU Fall Meeting","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Downscaling; Scale (ratio); Range (aeronautics); Environmental science; Domain (mathematical analysis); Geology; Climatology; Remote sensing; Oceanography; Climate change; Geography; Cartography; Mathematics; Engineering; Aerospace engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005699224,0.0001733179,0.0002355484,0.00002775569,0.0004183521,0.00007246236,0.000179508,0.00008567443,0.0003785838],"category_scores_gemma":[0.0001023673,0.0001464286,0.00009668871,0.0001498425,0.00008451462,0.0001351906,0.00003544685,0.0001492205,0.00028053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000012411,"about_ca_system_score_gemma":0.000009965696,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02441562,"about_ca_topic_score_gemma":0.04561289,"domain_scores_codex":[0.9985101,0.0001068889,0.000309007,0.000344961,0.0002907067,0.0004382997],"domain_scores_gemma":[0.9992357,0.0002730331,0.000120916,0.0002080412,0.00004087517,0.0001214217],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002763076,0.00002411683,0.9832374,0.00001812065,0.0000199698,0.000002643501,0.0002389563,0.002024523,0.0001498566,0.0004276395,0.003735746,0.01009339],"study_design_scores_gemma":[0.0004521587,0.00005586108,0.9064847,0.00003925869,0.00001958763,0.000003388737,0.0002718243,0.07458192,0.00000519886,0.0006851071,0.01719262,0.0002083461],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9873087,0.0005590218,0.003597539,0.0004992489,0.0005848529,0.0001511106,0.00004176318,0.0001059122,0.007151797],"genre_scores_gemma":[0.9896754,0.00005259735,0.009051925,0.0004148738,0.0004730432,0.000003552531,0.0001145401,0.000007834675,0.0002062085],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07675268,"threshold_uncertainty_score":0.9820809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008476876478746611,"score_gpt":0.2057110483581333,"score_spread":0.1972341718793866,"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."}}