{"id":"W2038871678","doi":"10.1117/12.2054415","title":"Strategies to cope with sodium layer profile variations in laser guide star AO systems","year":2014,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Adaptive optics and wavefront sensing","field":"Physics and Astronomy","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ontario Ministry of Research and Innovation; British Columbia Knowledge Development Fund; Natural Sciences and Engineering Research Council of Canada; National Astronomical Observatory of Japan; Association of Canadian Universities for Research in Astronomy; California Institute of Technology; Gordon and Betty Moore Foundation; National Science Foundation","keywords":"Tilt (camera); Deconvolution; Pixel; Computer science; Laser guide star; Optics; Laser; Adaptive optics; Telescope; Frame (networking); Remote sensing; Guide star; Lidar; Algorithm; Computer vision; Geology; Physics; Mathematics; Geometry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001133645,0.0008080859,0.0005510724,0.0008335182,0.0007216773,0.0007175236,0.001586961,0.0008782867,0.001017612],"category_scores_gemma":[0.003455797,0.0005235616,0.0005369966,0.000391742,0.0004404001,0.001507714,0.001529255,0.00096768,0.0005434375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005809864,"about_ca_system_score_gemma":0.001428607,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007258694,"about_ca_topic_score_gemma":0.009651161,"domain_scores_codex":[0.999566,0.0000749396,0.00002611525,0.00009840248,0.0001716238,0.00006297957],"domain_scores_gemma":[0.9989674,0.0002548304,0.0002057352,0.0001962984,0.0003132615,0.00006239173],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002740468,0.0002024645,0.01186851,0.0002000531,0.0001701925,0.000222297,0.0007559528,0.2757891,0.1567113,0.007627685,0.001609962,0.5445685],"study_design_scores_gemma":[0.00003798711,0.0001849905,0.004075348,0.0000174681,0.00004823528,0.000216337,0.0001719898,0.9377974,0.04774315,0.005248359,0.004404258,0.00005441931],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03480418,0.0001402715,0.9631436,0.0001203371,0.00002257739,0.00006609879,0.00002207568,0.00074585,0.0009349945],"genre_scores_gemma":[0.3188422,0.0001183983,0.6790356,0.0001099312,0.00002942362,0.0001287156,0.00009519181,0.0001425174,0.001498126],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007258694,"threshold_uncertainty_score":0.01443285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009885229065701592,"score_gpt":0.2257458665006322,"score_spread":0.2158606374349306,"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."}}