{"id":"W4402572337","doi":"10.1109/newcas58973.2024.10666337","title":"Design of a Reconfigurable Activation Function for All-Optical Neural Networks","year":2024,"lang":"en","type":"article","venue":"","topic":"Neural Networks and Reservoir Computing","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Activation function; Artificial neural network; Computer science; Function (biology); Computer architecture; Artificial intelligence","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":[0.0002159356,0.0003608669,0.0002226041,0.0001810155,0.0002909515,0.0004647588,0.0009923975,0.0005964322,0.001505897],"category_scores_gemma":[0.0003085921,0.0001828677,0.000221386,0.0001502414,0.000324486,0.0005127928,0.0003462749,0.0005443671,0.0004434617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000560938,"about_ca_system_score_gemma":0.0005792395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007129503,"about_ca_topic_score_gemma":0.001429694,"domain_scores_codex":[0.9999115,0.00001623316,0.000005283672,0.00002102635,0.00002316229,0.00002286209],"domain_scores_gemma":[0.9999214,0.00002053595,0.00001313772,0.000009242659,0.00002494048,0.00001073545],"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":[0.0002954373,0.0001893325,0.0009017715,0.0002068464,0.00006069044,0.000365081,0.0001423747,0.4675273,0.2456346,0.06557538,0.003130476,0.2159707],"study_design_scores_gemma":[0.00001239814,0.00006755324,0.0001037876,0.000008404985,0.000009527801,0.00006370441,0.00001118217,0.9526718,0.03957102,0.004094607,0.003375747,0.00001020111],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08891664,0.0004631705,0.8964288,0.0005525158,0.0001111304,0.00006811856,0.00005720294,0.001041145,0.01236125],"genre_scores_gemma":[0.8356796,0.0001830968,0.1599609,0.0001271911,0.00001775721,0.00009240834,0.00003725369,0.00005906806,0.003842789],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001505897,"threshold_uncertainty_score":0.005037785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03856909406393426,"score_gpt":0.2608287047395608,"score_spread":0.2222596106756265,"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."}}