{"id":"W2535105157","doi":"10.1093/mnras/stw3083","title":"Statistics of turbulence parameters at Maunakea using the multiple wavefront sensor data of RAVEN","year":2016,"lang":"en","type":"article","venue":"Monthly Notices of the Royal Astronomical Society","topic":"Adaptive optics and wavefront sensing","field":"Physics and Astronomy","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria; Herzberg Institute of Astrophysics","funders":"Agence Nationale de la Recherche","keywords":"Physics; Adaptive optics; Wavefront; Telescope; Turbulence; Scale (ratio); Prime (order theory); Sky; Subaru Telescope; Deformable mirror; Remote sensing; Algorithm; Optics; Statistics; Astrophysics; Meteorology; Computer science; Astronomy; Mathematics; Geography","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":[0.0002610118,0.0001880639,0.0003654957,0.000007440112,0.00013344,0.0000114526,0.0007066153,0.0000482827,0.00003972196],"category_scores_gemma":[0.00003929284,0.00009831905,0.0002624738,0.00004169572,0.000647712,0.00007362255,0.0008621708,0.0001209652,0.000001823929],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006633029,"about_ca_system_score_gemma":0.00005186241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009794373,"about_ca_topic_score_gemma":0.000020788,"domain_scores_codex":[0.9986195,0.00009004008,0.000491043,0.0002851338,0.0002288978,0.0002854154],"domain_scores_gemma":[0.9977635,0.000603625,0.0006555482,0.0008280301,0.0000900377,0.00005931134],"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":[0.0001098182,0.0001529705,0.1067338,0.0000294752,0.0004415682,7.178028e-8,0.0004350736,0.8865665,0.002205809,0.000279225,0.000616695,0.002429084],"study_design_scores_gemma":[0.0005858679,0.00004130507,0.02772061,0.00008927848,0.0001780733,8.687684e-9,0.0006206898,0.963434,0.006901606,0.0001005994,0.0001830346,0.0001449049],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9663306,0.00002974798,0.03010886,0.0001517764,0.0001276463,0.0002285841,0.002956939,0.000003640899,0.00006215202],"genre_scores_gemma":[0.9099063,1.521175e-7,0.0898503,0.000006892169,0.00006856429,0.000001015206,0.00002531574,0.00001785378,0.0001236106],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07901315,"threshold_uncertainty_score":0.4009335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03149065607575165,"score_gpt":0.2416535369794952,"score_spread":0.2101628809037435,"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."}}