{"id":"W3190162753","doi":"10.5194/amt-2021-2","title":"Assessing synergistic radar and radiometer capability in retrieving ice cloud microphysics based on hybrid Bayesian algorithms","year":2021,"lang":"en","type":"article","venue":"","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Goddard Space Flight Center; Stony Brook University; Nuclear Safety and Security Commission; National Center for Atmospheric Research; Environment and Climate Change Canada; Colorado State University; National Aeronautics and Space Administration","keywords":"Environmental science; Radiometer; Radar; Remote sensing; Computer science; Cloud computing; Brightness temperature; Algorithm; Meteorology; Precipitation; Ice cloud; Bayesian probability; Geology; Artificial intelligence; Geography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.004250894,0.001030029,0.0007686151,0.001234487,0.0004302867,0.000962887,0.0009760076,0.0009690315,0.000510443],"category_scores_gemma":[0.005972246,0.000648967,0.001056499,0.0008087777,0.0004605058,0.001780163,0.00131138,0.0007558556,0.000155616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007693336,"about_ca_system_score_gemma":0.001036779,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01026042,"about_ca_topic_score_gemma":0.008403543,"domain_scores_codex":[0.9990977,0.0003764037,0.0000536681,0.0001273213,0.0002540788,0.00009078599],"domain_scores_gemma":[0.9972894,0.001723706,0.0002531958,0.0001599332,0.0004825831,0.00009115891],"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":[0.0002536372,0.0002291681,0.01193445,0.00006026067,0.0002103958,0.00003573409,0.00005226498,0.9242805,0.004017842,0.002312187,0.0001916492,0.05642201],"study_design_scores_gemma":[0.00001260181,0.00003291677,0.000595448,0.000002626077,0.00001778859,0.000005688731,0.000005101082,0.9983279,0.0006737379,0.0002753812,0.00004368001,0.000007131294],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.506662,0.000743756,0.4880738,0.0002512304,0.00003716976,0.0001854517,0.0001486867,0.0003564901,0.003541574],"genre_scores_gemma":[0.854219,0.0001543212,0.1448135,0.00006469096,0.00002285126,0.00008979301,0.0002028817,0.00002888824,0.0004042125],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01026042,"threshold_uncertainty_score":0.02248114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0101208616398022,"score_gpt":0.2361113111107877,"score_spread":0.2259904494709855,"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."}}