{"id":"W3119680327","doi":"10.1364/ao.413848","title":"Polarimetric LiDAR backscattering contrast of linearly and circularly polarized pulses for ideal depolarizing targets in generic water fogs","year":2021,"lang":"en","type":"article","venue":"Applied Optics","topic":"Optical Polarization and Ellipsometry","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Optics; Lidar; Polarimetry; Circular polarization; Linear polarization; Contrast (vision); Polarization (electrochemistry); Materials science; Physics; Scattering; Laser","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":[0.0002044574,0.0002194279,0.000422329,0.0003017071,0.00006273316,0.0001053853,0.0001144712,0.0002049698,0.0000138345],"category_scores_gemma":[0.00008227964,0.0002189561,0.00007002332,0.0005487842,0.00004851632,0.0001326817,0.00007354569,0.0002468905,0.000009938282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004386483,"about_ca_system_score_gemma":0.00002883448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003260301,"about_ca_topic_score_gemma":0.00001233101,"domain_scores_codex":[0.9985762,0.00001531063,0.0005045069,0.0002651862,0.0001694438,0.0004694159],"domain_scores_gemma":[0.9994078,0.0001268814,0.0000382233,0.0002101011,0.0000853563,0.0001316931],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001666524,0.00005219892,0.003933961,0.0002728029,0.00007249662,0.000007759561,0.0001854496,0.000512497,0.9918616,0.002106454,0.000003320347,0.0009747597],"study_design_scores_gemma":[0.004479444,0.0001032476,0.0195293,0.00007779597,0.0001818725,0.00003813071,0.0003820303,0.05602069,0.9155288,0.001543775,0.00104183,0.00107305],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.49376,0.002461997,0.5020317,0.00008902908,0.0002715923,0.0004047683,0.00004880485,0.0001248606,0.0008072467],"genre_scores_gemma":[0.9572502,0.0001023731,0.04225831,0.000123678,0.00008463212,0.00001491855,0.00008036718,0.0000663455,0.00001921507],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4634902,"threshold_uncertainty_score":0.8928773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01097262663593165,"score_gpt":0.2087362306014451,"score_spread":0.1977636039655134,"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."}}