{"id":"W7004882916","doi":"","title":"Optical neural networks using Mach-Zehnder-based optical processors","year":2020,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Artificial neural network; Flexibility (engineering); Convolutional neural network; Time delay neural network; Network topology; Computation; Cellular neural network; Deep learning","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":[0.0001829427,0.0002536775,0.0001642552,0.0002850156,0.0002520185,0.0006878577,0.0006830244,0.000522675,0.002692797],"category_scores_gemma":[0.0005631945,0.0001880063,0.0002670756,0.0002992472,0.0004883517,0.0009989005,0.0003342337,0.0005399396,0.0005048383],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008648142,"about_ca_system_score_gemma":0.0004060692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001382108,"about_ca_topic_score_gemma":0.002750306,"domain_scores_codex":[0.9998875,0.00002270381,0.000004740902,0.00001923909,0.00005328335,0.00001255102],"domain_scores_gemma":[0.9998776,0.00005023956,0.00001855548,0.00001477691,0.00003354831,0.000005259151],"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":[0.000227244,0.0001681481,0.001016281,0.000310193,0.00007121139,0.0002015197,0.0002222804,0.3794263,0.1043099,0.2802671,0.00645911,0.2273206],"study_design_scores_gemma":[0.00002396947,0.00009948317,0.0002209797,0.00002443904,0.00001135731,0.00004836826,0.00002961803,0.955403,0.01679885,0.01541143,0.01191272,0.00001586121],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08175918,0.001880491,0.8576236,0.0009568827,0.000365326,0.00015673,0.0001069004,0.001163224,0.05598756],"genre_scores_gemma":[0.6502434,0.001473582,0.3290792,0.0003016313,0.00009581988,0.0002024394,0.0001079389,0.0000545398,0.01844143],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002692797,"threshold_uncertainty_score":0.009008288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05161928735901068,"score_gpt":0.2346828517418228,"score_spread":0.1830635643828121,"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."}}