{"id":"W2898413423","doi":"10.1364/fio.2018.jw4a.28","title":"Toward Training a Deep Neural Network to Optimize Lens Designs","year":2018,"lang":"en","type":"article","venue":"Frontiers in Optics / Laser Science","topic":"Advanced optical system design","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Citation; Computer science; Artificial neural network; Publishing; Artificial intelligence; World Wide Web","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":[0.0007478463,0.001250179,0.0005292945,0.0006147241,0.0002916944,0.0008264753,0.0008330247,0.00134109,0.003206],"category_scores_gemma":[0.002593761,0.0008015793,0.0006014738,0.0003981484,0.0004247611,0.001130102,0.0007648202,0.001264777,0.001155041],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001270992,"about_ca_system_score_gemma":0.001252095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006703676,"about_ca_topic_score_gemma":0.01218128,"domain_scores_codex":[0.9998156,0.00003975869,0.00001027172,0.00004834229,0.00005644504,0.00002958311],"domain_scores_gemma":[0.999551,0.0002077729,0.00004858181,0.00003264264,0.0001333395,0.00002662665],"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":[0.0001019413,0.00005924774,0.001111682,0.00007856015,0.00004914856,0.00003806087,0.00003453854,0.8535957,0.007068907,0.003188814,0.005049006,0.1296245],"study_design_scores_gemma":[0.000005867313,0.00001481766,0.0000505382,0.000007029015,0.000004738499,0.000004509794,0.000004078263,0.9971814,0.001243348,0.00102096,0.0004603241,0.000002365512],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05016082,0.001231792,0.9354708,0.0008186951,0.0001283918,0.0001034951,0.0003361481,0.002745012,0.009004836],"genre_scores_gemma":[0.5191929,0.0005446602,0.4684342,0.000523182,0.00008286476,0.0002288299,0.0006315153,0.0004334499,0.009928343],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006703676,"threshold_uncertainty_score":0.01332933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04343820309965908,"score_gpt":0.2485424672170109,"score_spread":0.2051042641173518,"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."}}