{"id":"W4405490664","doi":"10.1109/iccp63557.2024.10793041","title":"Advanced Performance Estimation of Analog Layouts Using Convolutional Neural Networks","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Optical Network Technologies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Convolutional neural network; Computer science; Artificial intelligence; Estimation; Artificial neural network; Pattern recognition (psychology); Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002923573,0.001151167,0.0002977015,0.0008625955,0.0001761336,0.0005789823,0.0008473768,0.0004736434,0.001901067],"category_scores_gemma":[0.00187357,0.000460429,0.0003352629,0.0005270464,0.0003068522,0.00102591,0.0003817593,0.0004978478,0.0004647968],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001195363,"about_ca_system_score_gemma":0.0005938955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005970205,"about_ca_topic_score_gemma":0.01122128,"domain_scores_codex":[0.999806,0.00002891799,0.000009831827,0.00004867597,0.00008317647,0.00002341652],"domain_scores_gemma":[0.9994661,0.0001997378,0.000108815,0.00008423477,0.0001218102,0.00001933872],"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":[0.00003345986,0.00002231355,0.001888908,0.00003764943,0.00002929527,0.00004931836,0.00001291314,0.9455685,0.007586489,0.001746611,0.000520755,0.04250374],"study_design_scores_gemma":[0.000001181276,0.000006586858,0.0002982447,0.000002893778,0.000003098235,0.000007904788,0.000001414153,0.9967013,0.002094844,0.0006949087,0.0001847102,0.000002840748],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1282478,0.0006017656,0.8610838,0.000185367,0.00004042906,0.00004140052,0.000482624,0.003648007,0.005668808],"genre_scores_gemma":[0.9255074,0.0003243834,0.07105733,0.00005703788,0.00002406789,0.00003915026,0.0004053726,0.0001251051,0.002460231],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005970205,"threshold_uncertainty_score":0.01187092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01111230748793848,"score_gpt":0.2378513096852033,"score_spread":0.2267390021972648,"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."}}