{"id":"W2972715463","doi":"10.5194/amt-12-4949-2019","title":"Calibration of the 2007–2017 record of Atmospheric Radiation Measurements cloud radar observations using CloudSat","year":2019,"lang":"en","type":"article","venue":"Atmospheric measurement techniques","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Office of Science; U.S. Department of Energy","keywords":"Radar; Environmental science; Remote sensing; Calibration; Cloud computing; Meteorology; Computer science; Geology; Geography; Telecommunications; Physics","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001191997,0.0003450363,0.0004688548,6.872575e-7,0.0001962937,0.00002334644,0.0007103682,0.000190879,0.001316513],"category_scores_gemma":[0.0001027158,0.0002745988,0.0002401477,0.000863491,0.0002218999,0.0004131768,0.0002470492,0.0001895074,0.00001850955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006802574,"about_ca_system_score_gemma":0.0001226812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002632647,"about_ca_topic_score_gemma":0.00008652385,"domain_scores_codex":[0.9961606,0.0002585333,0.0009417786,0.000492608,0.001752515,0.0003939873],"domain_scores_gemma":[0.9977042,0.00003378141,0.001048997,0.0009621576,0.000158327,0.00009250319],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005352693,0.0002403267,0.682299,0.00006548791,0.00008031185,3.88173e-7,0.0002243077,0.001871508,0.2915678,0.0001511373,0.006051462,0.01739472],"study_design_scores_gemma":[0.002354519,0.001224741,0.4661727,0.000871195,0.0005936599,0.00001611392,0.0005960397,0.0462043,0.4134676,0.002609385,0.06382232,0.002067459],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9538209,0.000351205,0.03648813,0.0001282596,0.0008581373,0.001806408,0.00000585565,0.0001567162,0.006384387],"genre_scores_gemma":[0.8472185,0.0001012131,0.1519168,0.0002097718,0.00008925794,0.00004622807,0.000004195986,0.00004925776,0.0003647361],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2161263,"threshold_uncertainty_score":0.9999706,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04799017349858303,"score_gpt":0.2428861241514585,"score_spread":0.1948959506528755,"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."}}