{"id":"W4404597520","doi":"10.1117/1.oe.63.11.115103","title":"Learning-based wide-angle optical design distortion optimization for improved monocular depth estimation","year":2024,"lang":"en","type":"article","venue":"Optical Engineering","topic":"Advanced optical system design","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Computer science; Distortion (music); Monocular; Optical engineering; Optics; Artificial intelligence; Computer vision; Telecommunications","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":[0.0003199349,0.0003269603,0.0003035129,0.0001600784,0.00006813464,0.0001771979,0.0001239773,0.0002218588,0.00001955415],"category_scores_gemma":[0.000760559,0.0003419312,0.0001437966,0.0003362814,0.0000283599,0.000356822,0.0000162497,0.0003255321,0.00003308078],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000390624,"about_ca_system_score_gemma":0.00003259899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.740915e-7,"about_ca_topic_score_gemma":2.605661e-7,"domain_scores_codex":[0.9984681,0.00001553854,0.0004354433,0.0003780198,0.0001925065,0.0005104156],"domain_scores_gemma":[0.9987298,0.0007609844,0.00001958557,0.0002043407,0.00006423652,0.0002210017],"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":[0.00001917144,0.0000160725,0.000001541749,0.0003846315,0.00004353255,0.000007870331,0.00001685499,0.9775532,0.006906876,0.001689165,0.00004167204,0.01331934],"study_design_scores_gemma":[0.0003154435,0.0001706503,0.00001420478,0.0001669174,0.00007435771,0.000006064614,0.000004288989,0.9842616,0.01380583,0.00009953895,0.0006869151,0.0003942153],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0005823825,0.0003834231,0.9953134,0.00009024619,0.000548558,0.0007754089,0.000004204182,0.002106195,0.0001961977],"genre_scores_gemma":[0.456883,0.000006595002,0.5425377,0.000007865878,0.00009652723,0.0002562795,0.00005397572,0.0001269486,0.00003118349],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4563006,"threshold_uncertainty_score":0.9999033,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009559175414401945,"score_gpt":0.2167176727966065,"score_spread":0.2071584973822046,"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."}}