{"id":"W3180565565","doi":"10.3390/app11136232","title":"Photonic Integrated Reconfigurable Linear Processors as Neural Network Accelerators","year":2021,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Neural Networks and Reservoir Computing","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Ministero dell’Istruzione, dell’Università e della Ricerca; Ministère de l'Économie, de la Science et de l'Innovation - Québec","keywords":"Photonics; Computer science; Silicon on insulator; Silicon; Silicon photonics; Optoelectronics; Electronic engineering; Materials science; 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":[0.00009608179,0.0001915173,0.0001263903,0.0001611636,0.0001488009,0.0005063694,0.0005876942,0.0003346013,0.002905602],"category_scores_gemma":[0.0002156287,0.0001462312,0.0001379384,0.0002035884,0.0002717229,0.0005282112,0.0002832734,0.0003527816,0.0005338686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003428441,"about_ca_system_score_gemma":0.0002566022,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004054105,"about_ca_topic_score_gemma":0.0008395475,"domain_scores_codex":[0.9998912,0.00001214042,0.000003752387,0.00001976472,0.0000473043,0.00002588359],"domain_scores_gemma":[0.9999092,0.00002826992,0.00001896277,0.00001410592,0.00002182135,0.000007691771],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000604633,0.0002507254,0.001218552,0.0002874833,0.00009485347,0.0003656448,0.0001324801,0.0902315,0.752228,0.05080929,0.004882825,0.09889401],"study_design_scores_gemma":[0.00006199948,0.0004882355,0.00149711,0.00002823806,0.00004475431,0.0002502939,0.00006991895,0.5518557,0.4187392,0.008158784,0.01876791,0.00003777283],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.679191,0.001990186,0.2553089,0.0007127107,0.0003797772,0.00009004272,0.0003315943,0.003567607,0.05842821],"genre_scores_gemma":[0.9558167,0.0003656019,0.03561831,0.0001122067,0.00002819292,0.00004691868,0.000118905,0.00006319863,0.007829989],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002905602,"threshold_uncertainty_score":0.009720206,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02571606081219082,"score_gpt":0.2601914235928488,"score_spread":0.234475362780658,"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."}}