{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000493177,0.0004109359,0.0003423416,0.0005215396,0.0003157516,0.000568865,0.00049572,0.0004791538,0.000999806],"category_scores_gemma":[0.004147469,0.0002893376,0.0003125726,0.0003893672,0.0004753099,0.001543576,0.0006705924,0.0005008085,0.0005097283],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006010283,"about_ca_system_score_gemma":0.0003292553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005945443,"about_ca_topic_score_gemma":0.0008211836,"domain_scores_codex":[0.999786,0.00002477066,0.00001461744,0.00006034343,0.00007767086,0.00003652841],"domain_scores_gemma":[0.9988247,0.0007538113,0.0001888345,0.00009607231,0.00009865309,0.00003786282],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00023699,0.0002133271,0.08110473,0.0004030901,0.0001090908,0.002328548,0.0004038749,0.4943144,0.2494077,0.08279593,0.0007114481,0.08797085],"study_design_scores_gemma":[0.0000249618,0.0001161085,0.01551371,0.00004198385,0.00002302226,0.002277648,0.00007324795,0.8964417,0.03712624,0.04654365,0.001716399,0.0001014038],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5794077,0.001782991,0.4117544,0.0003201065,0.00004761052,0.00009690655,0.0001743545,0.0003204198,0.006095472],"genre_scores_gemma":[0.9839081,0.0004929863,0.01468343,0.00004133628,0.00001339653,0.00002219529,0.00006823981,0.00003358905,0.0007367401],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.000999806,"threshold_uncertainty_score":0.004360735,"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."}}