{"id":"W4290717181","doi":"10.1364/cleo_si.2022.ss2b.2","title":"Time Series Prediction and Classification using Silicon Photonic Neuron with a Self-Connection","year":2022,"lang":"en","type":"article","venue":"Conference on Lasers and Electro-Optics","topic":"Neural Networks and Reservoir Computing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Photonics; Connection (principal bundle); Computer science; Series (stratigraphy); Silicon photonics; Recurrent neural network; Series and parallel circuits; Artificial neural network; Artificial intelligence; Electronic engineering; Engineering; Electrical engineering; Optoelectronics; Materials science; Voltage","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":[],"consensus_categories":[],"category_scores_codex":[0.0001459503,0.000147653,0.0001408112,0.00008279526,0.0006099824,0.0002099842,0.0001617049,0.00003850888,0.000005729617],"category_scores_gemma":[0.000004638298,0.0001299884,0.00001851019,0.0002715591,0.00005322746,0.0003031808,0.0001314034,0.0002754267,0.000001008093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005588383,"about_ca_system_score_gemma":0.00008329048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007136412,"about_ca_topic_score_gemma":0.000003254577,"domain_scores_codex":[0.9988929,0.00009167629,0.0001431148,0.0004093252,0.00019618,0.0002667923],"domain_scores_gemma":[0.9995082,0.00004235845,0.0001072869,0.0002080576,0.00005600446,0.00007809499],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001332504,0.0009417239,0.004922483,0.0003064302,0.0003201545,0.0001606337,0.004179167,0.1082711,0.5533983,0.2506886,0.001061549,0.07441738],"study_design_scores_gemma":[0.0002935299,0.001476356,0.0006573296,0.00001807808,0.00001656794,0.000141448,0.00009162128,0.9947201,0.00148061,0.0005853821,0.0003659824,0.0001529739],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9906995,0.00005778814,0.007372091,0.0009248322,0.0001249076,0.0002161827,0.000002619918,0.00016717,0.0004348826],"genre_scores_gemma":[0.9978067,0.0001563253,0.001671114,0.0001563518,0.00005082765,0.00001491521,0.000006863334,0.00001128008,0.0001255702],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.886449,"threshold_uncertainty_score":0.5300772,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01777559695953299,"score_gpt":0.2157111357091979,"score_spread":0.197935538749665,"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."}}