{"id":"W4308514394","doi":"10.1364/optica.475493","title":"Silicon photonic architecture for training deep neural networks with direct feedback alignment","year":2022,"lang":"en","type":"article","venue":"Optica","topic":"Neural Networks and Reservoir Computing","field":"Computer Science","cited_by":91,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; University of British Columbia; Queen's University","funders":"Air Force Office of Scientific Research; Natural Sciences and Engineering Research Council of Canada; Queen's University; Canada Foundation for Innovation","keywords":"Training (meteorology); Architecture; Artificial neural network; Computer science; Computer architecture; Photonics; Artificial intelligence; Optoelectronics; Materials science; Physics; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002651931,0.0001918124,0.000228398,0.00005011074,0.0006322347,0.0001670682,0.0008441732,0.0000306847,0.0000208068],"category_scores_gemma":[0.00000790752,0.0001493873,0.0001104339,0.000359208,0.00003948669,0.00008631588,0.0005282633,0.0003222346,8.303315e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005403954,"about_ca_system_score_gemma":0.00003118254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006069912,"about_ca_topic_score_gemma":0.00001085559,"domain_scores_codex":[0.9982883,0.00008860733,0.0001917235,0.0005210547,0.0002969451,0.0006134151],"domain_scores_gemma":[0.9990614,0.0002616947,0.00009321795,0.0004299596,0.00002583004,0.0001278901],"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":[0.00004084896,0.00003175796,0.00002849153,0.00000734219,0.00002635813,0.0000292457,0.0005481503,0.9324143,0.0001173997,0.0009820799,0.0001901871,0.06558383],"study_design_scores_gemma":[0.000478926,0.0005542707,0.00007049647,0.0000110011,0.00001079644,0.0000911032,0.00008700815,0.9914414,0.0000905938,0.0001810856,0.006754771,0.0002285525],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1106299,0.0007177967,0.8785151,0.004032251,0.00109169,0.001057053,0.000004206703,0.0003722362,0.003579776],"genre_scores_gemma":[0.9657197,0.000003584795,0.03296688,0.0007909889,0.000204364,0.0001362528,0.000005967999,0.00002456419,0.0001477164],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8550898,"threshold_uncertainty_score":0.6091835,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01419882078132518,"score_gpt":0.2194738990975723,"score_spread":0.2052750783162472,"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."}}