{"id":"W4380272255","doi":"10.23977/jeis.2023.080206","title":"Hardware Implementation of Artificial Synapses","year":2023,"lang":"en","type":"article","venue":"Journal of Electronics and Information Science","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Crossbar switch; Computer science; Line (geometry); Path (computing); Array data structure; Limiting; Computer hardware; Perpendicular; Word (group theory); Process (computing); Electrical engineering; Electronic engineering; Telecommunications; Engineering; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001096734,0.0002970063,0.0002500904,0.000237089,0.0002356356,0.0006447223,0.001901695,0.0005360891,0.005830552],"category_scores_gemma":[0.0003706515,0.0001919341,0.0001855356,0.0002274203,0.0001604044,0.0004713871,0.0002777038,0.0004050101,0.001568309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002708645,"about_ca_system_score_gemma":0.0003517423,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004243669,"about_ca_topic_score_gemma":0.0008356096,"domain_scores_codex":[0.9998794,0.00001222383,0.00001135731,0.00002070862,0.00005755122,0.00001881105],"domain_scores_gemma":[0.9998837,0.00002332971,0.00001203279,0.00002532812,0.00004400077,0.00001167208],"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":[0.0004314187,0.000298551,0.001135281,0.00100968,0.0001493345,0.0008459085,0.0001526403,0.08799668,0.4263188,0.09030021,0.01161563,0.3797459],"study_design_scores_gemma":[0.0001346789,0.0007551772,0.001389435,0.00009434355,0.00009426782,0.001060095,0.00003959748,0.7067989,0.2092652,0.01385258,0.06646138,0.00005436658],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09139764,0.0018389,0.8556665,0.0004289857,0.0008663086,0.0002304009,0.0003600704,0.007229868,0.04198131],"genre_scores_gemma":[0.7279997,0.0007877135,0.2598769,0.0002381854,0.00009394548,0.0002524629,0.0002746341,0.00007630054,0.01040003],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005830552,"threshold_uncertainty_score":0.01950514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01416584797975136,"score_gpt":0.2913609741101115,"score_spread":0.2771951261303602,"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."}}