{"id":"W1979060409","doi":"10.1175/2010jamc2505.1","title":"Uncertainty Analysis for CloudSat Snowfall Retrievals","year":2010,"lang":"en","type":"article","venue":"Journal of Applied Meteorology and Climatology","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":94,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Snow; Environmental science; Precipitation; Meteorology; Attenuation; Liquid water path; Radiometer; Radar; Climatology; Remote sensing; Geology; Computer science","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000878025,0.0001470595,0.000603868,0.00001184904,0.0001369744,0.00001011191,0.0002390348,0.0003120294,0.001242476],"category_scores_gemma":[0.00008357714,0.0001122116,0.0001918536,0.00026944,0.0005114462,0.00004868832,0.0000930381,0.0003904733,0.00001709025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001748939,"about_ca_system_score_gemma":0.00001778697,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000012531,"about_ca_topic_score_gemma":0.000163453,"domain_scores_codex":[0.9987811,0.00003637404,0.0004961824,0.0002339452,0.0001258119,0.0003265133],"domain_scores_gemma":[0.9988348,0.0003455181,0.0004621503,0.0001792845,0.00002849623,0.0001497769],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004656134,0.0004253803,0.7655881,0.0000372764,0.00223602,0.00006294101,0.001100386,0.004028502,0.1253137,0.07062056,0.007573429,0.01835757],"study_design_scores_gemma":[0.01075148,0.003466329,0.4144892,0.000006654055,0.007655251,0.00185138,0.001838811,0.006094608,0.009783611,0.1711916,0.3713758,0.001495283],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908403,0.00005933857,0.003803258,0.001006985,0.0003165453,0.0001251053,0.000004168819,0.000008557464,0.003835808],"genre_scores_gemma":[0.9862961,0.00008211187,0.01256598,0.0008980748,0.00008134363,0.000008880666,0.000002859108,0.000009410716,0.00005527415],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3638024,"threshold_uncertainty_score":0.9996705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007179686807898964,"score_gpt":0.2398370277971076,"score_spread":0.2326573409892087,"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."}}