{"id":"W4300816793","doi":"10.1117/12.2633916","title":"Photonic tensor core for machine learning: a review","year":2022,"lang":"en","type":"review","venue":"","topic":"Neural Networks and Reservoir Computing","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Scalability; Computer science; Photonics; Computer architecture; Bandwidth (computing); Electronic circuit; Multi-core processor; Photonic integrated circuit; Latency (audio); Limit (mathematics); Embedded system; Telecommunications; Electrical engineering; Engineering; Parallel computing; Physics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007724562,0.000462612,0.001834325,0.0001110917,0.0004094554,0.0001194263,0.002474783,0.0001071594,0.0004228215],"category_scores_gemma":[0.000147183,0.000302368,0.00114177,0.0008575339,0.00001878395,0.00008691512,0.001505224,0.0009203794,0.00004179404],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008447444,"about_ca_system_score_gemma":0.0002158902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008984654,"about_ca_topic_score_gemma":0.000001922208,"domain_scores_codex":[0.9973365,0.0002245458,0.0007181668,0.000865068,0.000332097,0.0005236277],"domain_scores_gemma":[0.9975762,0.0008783191,0.0005176961,0.0008551677,0.00004580348,0.0001267852],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[3.343585e-7,0.00001627306,1.327356e-7,0.0353565,0.00004100199,0.00001853601,0.000002580187,0.00002015176,7.877013e-9,0.001314718,0.01030644,0.9529233],"study_design_scores_gemma":[0.00007207804,0.0001211579,1.243028e-8,0.01527335,0.0001456789,0.0001655435,3.423488e-7,0.03507829,2.25047e-8,0.00006482337,0.9487048,0.0003738993],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[7.401151e-9,0.9830421,0.01252485,0.0002158481,0.0006062644,0.001987125,0.000006225895,0.0003239816,0.001293571],"genre_scores_gemma":[2.65843e-8,0.982821,0.008250196,0.0008311812,0.0001711935,0.0004346369,0.00008785479,0.00005083992,0.007353096],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9525494,"threshold_uncertainty_score":0.9999428,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1465184795659677,"score_gpt":0.3582927509244441,"score_spread":0.2117742713584764,"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."}}