{"id":"W2997601308","doi":"10.17586/2226-1494-2019-19-6-1022-1030","title":"Optimization techniques applied to initial designs of ultraviolet lithographic objectives","year":2019,"lang":"en","type":"article","venue":"Scientific and technical journal of information technologies mechanics and optics","topic":"Advancements in Photolithography Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"European Commission","keywords":"Computer science; Global optimization; Ray tracing (physics); Task (project management); Mathematical optimization; Lithography; Saddle point; Optimization problem; Point (geometry); Algorithm; Systems engineering; Engineering; Mathematics; Optics","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":[0.0006056567,0.0001519578,0.0002764822,0.001008631,0.00006886463,0.00009885002,0.000289202,0.0002070508,0.000003283145],"category_scores_gemma":[0.0001005909,0.0001310585,0.00005224963,0.0007798363,0.0001293101,0.000545143,0.0001210257,0.000269622,4.903355e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002416564,"about_ca_system_score_gemma":0.00001968572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":2.112977e-7,"about_ca_topic_score_gemma":1.627379e-7,"domain_scores_codex":[0.9987876,0.000008008707,0.0006487527,0.0001078879,0.0002737404,0.000174018],"domain_scores_gemma":[0.9991264,0.00004583797,0.0002676256,0.0002300819,0.000278076,0.00005200265],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000180523,0.0001431079,0.0002248958,0.0006872757,0.0001534269,0.000003620901,0.0005620311,0.01732961,0.169719,0.5146843,0.0003994623,0.2959128],"study_design_scores_gemma":[0.0009536218,0.001897078,0.0001665482,0.0006941091,0.0001094178,0.0002559733,0.004411693,0.02765178,0.8149568,0.1453232,0.002687061,0.0008927151],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02473457,0.0001551563,0.9728935,0.00003658629,0.0001951453,0.0004941269,0.00002192179,0.0005074366,0.0009615491],"genre_scores_gemma":[0.6799878,0.0007118575,0.3192578,0.00001456307,0.000003900822,0.00001137184,0.000003823557,0.00000781074,0.000001042848],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6552532,"threshold_uncertainty_score":0.5344409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007213155566921,"score_gpt":0.2305875029556746,"score_spread":0.2233743473887536,"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."}}