{"id":"W4281921892","doi":"10.1364/ao.458566","title":"Polarimetric multiple scattering LiDAR model based on Poisson distribution","year":2022,"lang":"en","type":"article","venue":"Applied Optics","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Lidar; Scattering; Optics; Remote sensing; Polarimetry; Poisson distribution; Physics; Monte Carlo method; Mie scattering; Aerosol; SIGNAL (programming language); Range (aeronautics); Forward scatter; Backscatter (email); Photon counting; Atmospheric optics; Field of view; Light scattering; Photon; Materials science; Meteorology; Geology; Computer science; Statistics","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":[0.0007039667,0.0008377846,0.0009194319,0.0008736341,0.000539152,0.001100379,0.002422134,0.001273057,0.001873795],"category_scores_gemma":[0.001345245,0.0004786581,0.0009056687,0.00121773,0.0008033541,0.001833324,0.0006717402,0.0007680463,0.0006957558],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009979402,"about_ca_system_score_gemma":0.0007709853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007006034,"about_ca_topic_score_gemma":0.002265056,"domain_scores_codex":[0.999373,0.0001211938,0.00002384114,0.000149603,0.0002374947,0.00009499284],"domain_scores_gemma":[0.9993203,0.0002496884,0.0001109726,0.00005151246,0.0002310311,0.00003649848],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007557726,0.00005240694,0.001893968,0.0001046766,0.00004068302,0.0005476225,0.0001390365,0.9228009,0.006899472,0.05863282,0.001376207,0.0074366],"study_design_scores_gemma":[0.000008683542,0.00001380432,0.0001755748,0.000004437907,0.000006118543,0.00009733765,0.00001022442,0.9934453,0.0003939748,0.005406117,0.0004266872,0.00001177465],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09697226,0.001332954,0.8814085,0.0006867558,0.000226729,0.0002273062,0.0009427695,0.000493763,0.01770893],"genre_scores_gemma":[0.9115959,0.002442347,0.05784037,0.0004419531,0.0002828087,0.000464189,0.0008360492,0.0001721754,0.02592413],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007006034,"threshold_uncertainty_score":0.01393056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008239178666373,"score_gpt":0.1964063364274909,"score_spread":0.1881671577611179,"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."}}