{"id":"W2042034950","doi":"10.1364/aopt.2007.atuc7","title":"Performance Assessment of Laser Guide Star Wave Front Sensing","year":2007,"lang":"en","type":"article","venue":"Adaptive Optics: Analysis and Methods/Computational Optical Sensing and Imaging/Information Photonics/Signal Recovery and Synthesis Topical Meetings on CD-ROM","topic":"Adaptive optics and wavefront sensing","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Wavefront; Laser guide star; Guide star; Computer science; Front (military); Adaptive optics; Laser; Star (game theory); Optics; Remote sensing; Simulation; Aerospace engineering; Physics; Engineering; Geology; Meteorology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001935071,0.0004026707,0.0008183538,0.0003922188,0.0004275684,0.0002349474,0.0000650771,0.0001034074,0.00003798736],"category_scores_gemma":[0.0002086501,0.0003577069,0.00023431,0.0002773874,0.0003024671,0.0005622576,0.0001159464,0.0003557143,0.000002264864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007743149,"about_ca_system_score_gemma":0.00008332191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002095202,"about_ca_topic_score_gemma":0.00001353239,"domain_scores_codex":[0.9973174,0.0001820456,0.001083728,0.0004836452,0.0004751753,0.0004579826],"domain_scores_gemma":[0.9953452,0.003087449,0.0005358423,0.0001754166,0.0005542758,0.0003018055],"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":[0.0003984942,0.0001837981,0.003423626,0.0000796543,0.001669814,0.00001154803,0.0007484473,0.01628874,0.003515021,0.01839987,0.00002150676,0.9552595],"study_design_scores_gemma":[0.0005344627,0.0001870271,0.07404926,0.0001858917,0.0008478567,0.00001492482,0.001329981,0.9148209,0.004522637,0.002487336,0.0005341028,0.0004855898],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5613175,0.00003021643,0.4298712,0.000172977,0.00005116659,0.0001565286,0.00002523664,0.00001736546,0.008357779],"genre_scores_gemma":[0.5767614,0.00002826693,0.4229188,0.0001679915,0.00004746599,7.637117e-7,0.00002727707,0.00001147885,0.00003652792],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9547739,"threshold_uncertainty_score":0.9998875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01275049435528908,"score_gpt":0.2819396384006358,"score_spread":0.2691891440453467,"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."}}