{"id":"W3012030487","doi":"10.1117/1.oe.59.3.034105","title":"Linear perturbation model for simulating imaging through weak turbulence","year":2020,"lang":"en","type":"article","venue":"Optical Engineering","topic":"Adaptive optics and wavefront sensing","field":"Physics and Astronomy","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Turbulence; Paraxial approximation; Physics; Perturbation (astronomy); Scalar field; Optics; Scalar (mathematics); Wavelength; Statistical physics; Computational physics; Classical mechanics; Mechanics; Mathematics; Geometry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003164472,0.0005346944,0.0004939443,0.0003596346,0.0003244467,0.0006156335,0.001119736,0.00102374,0.001493358],"category_scores_gemma":[0.00105004,0.0003215043,0.0004625218,0.000355168,0.0005392169,0.0009499947,0.0005375612,0.001067069,0.0003907704],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008691264,"about_ca_system_score_gemma":0.0007785017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005860386,"about_ca_topic_score_gemma":0.002120496,"domain_scores_codex":[0.9998196,0.00004840831,0.000006806335,0.0000225384,0.0000784619,0.00002426322],"domain_scores_gemma":[0.9994815,0.0002722484,0.00005304865,0.00002786399,0.0001210388,0.00004434892],"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":[0.00003023638,0.0000175547,0.0001550797,0.00002045289,0.000007454169,0.00005599415,0.00002162119,0.9774136,0.007005486,0.01222111,0.0003508055,0.002700674],"study_design_scores_gemma":[0.000001383944,0.000003918447,0.0000129046,4.867542e-7,7.173167e-7,0.000004541807,9.296961e-7,0.9990036,0.0003382111,0.0005186062,0.0001127548,0.000001869781],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02015104,0.0001425668,0.9734322,0.0002647713,0.00005807021,0.00006382572,0.00009791142,0.000505226,0.005284313],"genre_scores_gemma":[0.7685841,0.0006061036,0.2076804,0.0002700363,0.00009825586,0.0004001557,0.0003152571,0.0003490456,0.02169665],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005860386,"threshold_uncertainty_score":0.01165253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02240477785408526,"score_gpt":0.2450240809161143,"score_spread":0.222619303062029,"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."}}