{"id":"W2767970493","doi":"10.5194/amt-10-4253-2017","title":"Depolarization calibration and measurements using the CANDAC Rayleigh–Mie–Raman lidar at Eureka, Canada","year":2017,"lang":"en","type":"article","venue":"Atmospheric measurement techniques","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Dalhousie University; Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Space Agency; Indigenous and Northern Affairs Canada; Environment and Climate Change Canada; Eurostars; Strong; Ontario Innovation Trust","keywords":"Lidar; Depolarization ratio; Remote sensing; Environmental science; Calibration; Ice cloud; Rayleigh scattering; Depolarization; Optics; Physics; Geology; Radiative transfer","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0008299325,0.0002968548,0.0002233416,4.272821e-7,0.002094765,0.0002300939,0.0005380237,0.0001073381,0.000363186],"category_scores_gemma":[0.00009258476,0.0002220004,0.00004705489,0.0001093306,0.0003157573,0.0003766176,0.0004226515,0.0001504488,0.000003233484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001532329,"about_ca_system_score_gemma":0.0001801819,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.4948741,"about_ca_topic_score_gemma":0.4509813,"domain_scores_codex":[0.9972946,0.000132889,0.0003505136,0.0004674616,0.001353372,0.0004011397],"domain_scores_gemma":[0.9985763,0.00001450684,0.000408481,0.0007883506,0.00005930365,0.0001530002],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002855539,0.00004388905,0.8977747,0.00001646806,0.00005003028,0.000007847962,0.0001446891,0.0001727218,0.08379902,0.0000424544,0.005519125,0.01240051],"study_design_scores_gemma":[0.00108582,0.0002822372,0.7106571,0.0002075227,0.0003227966,0.00005457217,0.0003058011,0.02494177,0.2078476,0.0006076703,0.05197831,0.001708834],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9467005,0.000386619,0.04405749,0.0009426153,0.0003113699,0.001128328,0.000004820502,0.0001808397,0.006287438],"genre_scores_gemma":[0.9854187,0.00005023602,0.01348158,0.0005630048,0.00007697548,0.00005453945,0.000003532251,0.0000388515,0.000312549],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1871176,"threshold_uncertainty_score":0.9992044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03523181252701652,"score_gpt":0.2357692126301827,"score_spread":0.2005374001031662,"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."}}