{"id":"W2013814717","doi":"10.1364/josaa.25.002271","title":"Woofer-tweeter control in an adaptive optics system using a Fourier reconstructor","year":2008,"lang":"en","type":"article","venue":"Journal of the Optical Society of America A","topic":"Adaptive optics and wavefront sensing","field":"Physics and Astronomy","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Herzberg Institute of Astrophysics; Université de Montréal","funders":"","keywords":"Adaptive optics; Computer science; Fast Fourier transform; Deformable mirror; Fourier transform; Monte Carlo method; Optics; Physics; Control theory (sociology); Algorithm; Control (management); Artificial intelligence; 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":[0.0002198067,0.0001641694,0.0005338492,0.00002978615,0.0001354582,0.00001857295,0.0002230287,0.00005996515,0.00001735878],"category_scores_gemma":[0.000012232,0.0001132294,0.000546803,0.0001730048,0.0004569766,0.0001815836,0.00005510073,0.0004167029,0.000001065285],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000116925,"about_ca_system_score_gemma":0.0001662327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005222512,"about_ca_topic_score_gemma":2.472796e-7,"domain_scores_codex":[0.9985743,0.00009839398,0.0005998642,0.0001320478,0.0003277413,0.0002676706],"domain_scores_gemma":[0.9985918,0.0001408188,0.0006596817,0.0001950632,0.0002782701,0.0001343419],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004852783,0.006012562,0.5369723,0.0003394284,0.009552055,0.0002607206,0.03579938,0.14768,0.1479848,0.03901494,0.004034094,0.06749686],"study_design_scores_gemma":[0.004174548,0.00111248,0.01193484,0.0006344806,0.0004046973,0.0002530297,0.02175218,0.9562132,0.001583311,0.001083262,0.0002712496,0.0005826881],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.882924,0.00003255695,0.1157225,0.0002120486,0.0001862077,0.0001318135,0.00001351541,0.000003337908,0.0007740372],"genre_scores_gemma":[0.8368376,0.00000298523,0.162745,0.00008823541,0.000289472,4.183346e-7,2.472294e-7,0.00001605916,0.00001994231],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8085332,"threshold_uncertainty_score":0.461736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02426049761419211,"score_gpt":0.2431270040609153,"score_spread":0.2188665064467231,"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."}}