{"id":"W2030379029","doi":"10.1364/ol.31.001809","title":"Simple relation between lidar multiple scattering and depolarization for water clouds","year":2006,"lang":"en","type":"article","venue":"Optics Letters","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":117,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Lidar; Monte Carlo method; Scattering; Backscatter (email); Extinction (optical mineralogy); Mie scattering; Optics; Forward scatter; Physics; Remote sensing; Computational physics; Light scattering; Range (aeronautics); Atmospheric optics; Materials science; Geology; Statistics; Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.00007936388,0.00008764819,0.00007627584,0.000001263843,0.000161291,0.00004205529,0.00005645679,0.00004808162,0.00004350917],"category_scores_gemma":[0.000007071017,0.00007442557,0.00002463743,0.00003947064,0.00006689914,0.0001290047,0.00006263373,0.00004564921,0.0000267043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004521907,"about_ca_system_score_gemma":8.765846e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002021551,"about_ca_topic_score_gemma":0.00002279128,"domain_scores_codex":[0.9993687,0.000009780478,0.0001386148,0.0001797567,0.0001003945,0.0002027318],"domain_scores_gemma":[0.9997907,0.0000391542,0.0000355732,0.00009770521,0.000002906421,0.00003401071],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000003754016,0.000006992935,0.7036469,0.000004761195,0.000003608464,5.620669e-7,0.00008352077,0.005864492,0.2892138,0.00002597916,0.0003110347,0.0008345947],"study_design_scores_gemma":[0.0005876555,0.00004619901,0.9401848,0.000006781061,0.00004191608,0.000001979312,0.00002468609,0.02222368,0.03155443,0.0006520605,0.004383024,0.0002927967],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8835369,0.000003409614,0.1151278,0.000848211,0.0000377223,0.0001476132,0.000004295327,0.00002460955,0.0002694769],"genre_scores_gemma":[0.9806249,0.000001284057,0.01868887,0.0003637879,0.0001251738,0.00001068417,0.00007997684,0.00001744891,0.0000878762],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2576594,"threshold_uncertainty_score":0.3034987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007300911237927832,"score_gpt":0.199213116210294,"score_spread":0.1919122049723662,"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."}}