{"id":"W4313814540","doi":"10.1515/nanoph-2022-0553","title":"Photonic online learning: a perspective","year":2023,"lang":"en","type":"article","venue":"Nanophotonics","topic":"Neural Networks and Reservoir Computing","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; National Institute of Standards and Technology","keywords":"Neuromorphic engineering; Computer science; Perspective (graphical); Photonics; Computer architecture; Efficient energy use; Artificial neural network; Human–computer interaction; Artificial intelligence; Electrical engineering; Engineering; Physics","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":[0.00105668,0.0005069197,0.0005979551,0.0005753499,0.0008211405,0.002988467,0.001678831,0.003556539,0.006552813],"category_scores_gemma":[0.002690385,0.0003470377,0.0004317706,0.0004260389,0.003832327,0.007370254,0.001419425,0.004940781,0.001231133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00171238,"about_ca_system_score_gemma":0.001017211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000822654,"about_ca_topic_score_gemma":0.0006751614,"domain_scores_codex":[0.9993548,0.0001815558,0.00001732436,0.0001062356,0.0002649169,0.00007522546],"domain_scores_gemma":[0.9981754,0.001195153,0.00007809114,0.0002193751,0.0002377899,0.00009434675],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001129209,0.00004245963,0.00004323719,0.0001030876,0.000005263261,0.00003465328,0.00002907421,0.002071465,0.0004419372,0.9763812,0.003802755,0.01703358],"study_design_scores_gemma":[0.00001075069,0.00004834247,0.0001021494,0.0001073908,0.000006154167,0.0001033366,0.0000506777,0.02448684,0.0008504912,0.9215908,0.05262537,0.00001760895],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"commentary","genre_scores_codex":[0.01534293,0.1237465,0.3578436,0.1327784,0.006681357,0.0000659428,0.0002465583,0.0005544663,0.3627404],"genre_scores_gemma":[0.6878964,0.1063689,0.08565222,0.02496583,0.02315629,0.0003186041,0.0001794724,0.0002599295,0.07120244],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.006552813,"threshold_uncertainty_score":0.02192134,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01926823400906379,"score_gpt":0.2750197171007705,"score_spread":0.2557514830917067,"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."}}