{"id":"W4233354032","doi":"10.5194/tc-2018-112","title":"Estimation of sea ice parameters from sea ice model withassimilated ice concentration and SST","year":2018,"lang":"en","type":"preprint","venue":"","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Research and Development Corporation of Newfoundland and Labrador","keywords":"Sea ice; Sea ice thickness; Sea ice concentration; Freeboard; Radiometer; Keel; Geology; Environmental science; Climatology; Sea surface temperature; Arctic ice pack; Remote sensing; Atmospheric sciences; Oceanography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002927269,0.0006251817,0.0004764489,0.0003206023,0.0002834766,0.0005108928,0.0004656348,0.0004505556,0.0008261269],"category_scores_gemma":[0.0006859194,0.0003848996,0.0005406793,0.0002404853,0.0001808959,0.0003972194,0.0002417979,0.0004673042,0.0002882264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009359113,"about_ca_system_score_gemma":0.0008973415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04049274,"about_ca_topic_score_gemma":0.02943253,"domain_scores_codex":[0.999925,0.00001608632,0.000005086126,0.00002218988,0.0000171748,0.00001443689],"domain_scores_gemma":[0.9997861,0.00005703267,0.00002801001,0.00002661773,0.00008423314,0.00001801324],"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":[0.0000625171,0.00003847349,0.01301473,0.00001672624,0.0000435471,0.00003423649,0.00001324948,0.9784588,0.003123648,0.0001611113,0.0002871191,0.004745863],"study_design_scores_gemma":[0.00001491731,0.00001480644,0.005428388,0.000002693144,0.000006582456,0.000004781099,0.000004741522,0.9932851,0.0009920754,0.00005938244,0.0001805448,0.000006116454],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9707253,0.0001376774,0.0246528,0.00006356191,0.00002043938,0.00004439118,0.001771701,0.0005327427,0.002051355],"genre_scores_gemma":[0.9916242,0.00004588046,0.005596433,0.0000146567,0.000004560934,0.00003426131,0.001915603,0.00003887176,0.0007254821],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04049274,"threshold_uncertainty_score":0.08051407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02037964719389609,"score_gpt":0.2294463266864595,"score_spread":0.2090666794925634,"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."}}