{"id":"W4322762923","doi":"10.35848/1882-0786/acc0d2","title":"Demonstration of electronic synapses using a sericin-based bio-memristor","year":2023,"lang":"en","type":"article","venue":"Applied Physics Express","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Neuromorphic engineering; Memristor; Sericin; Materials science; Conductance; Voltage; Synaptic plasticity; Plasticity; Spike-timing-dependent plasticity; Optoelectronics; Neuroscience; Computer science; Biological system; Electronic engineering; Artificial neural network; Electrical engineering; SILK; Chemistry; Physics; Artificial intelligence; Engineering; Biology; Composite material","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":[0.00004171803,0.000117788,0.0001465977,0.0000380832,0.00004603433,0.000006746932,0.00008961725,0.00003513148,0.000001926289],"category_scores_gemma":[0.000001936718,0.0001306282,0.00003858469,0.0003517908,0.00002558411,0.00005717145,0.00001689705,0.0001143299,0.000008326572],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003601781,"about_ca_system_score_gemma":0.00001898438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000158587,"about_ca_topic_score_gemma":3.581736e-7,"domain_scores_codex":[0.9993785,0.000007447382,0.0001426317,0.0001320795,0.00009557867,0.0002437553],"domain_scores_gemma":[0.9996772,0.00008318273,0.00004494852,0.0001528855,0.00001602702,0.00002568955],"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":[0.00000533244,0.000005041305,0.000007035486,0.0000424557,0.000006526941,4.867659e-7,0.00003555495,0.4812652,0.5162917,0.001043485,0.00001759467,0.001279628],"study_design_scores_gemma":[0.0001373302,0.00001038493,0.00001509285,0.00001812079,0.00001027211,3.336475e-7,0.00003340117,0.2671135,0.7315288,0.0009457566,0.00007528265,0.0001116845],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8767347,0.00003061791,0.1220971,0.000001564084,0.00006909607,0.0001207269,0.000004284812,0.0003430733,0.0005987246],"genre_scores_gemma":[0.9989917,0.000004417953,0.000835757,0.00001156245,0.00009164061,0.00001221416,0.00001667958,0.00002985317,0.000006158351],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2152371,"threshold_uncertainty_score":0.5326865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01865041923339488,"score_gpt":0.23690276106097,"score_spread":0.2182523418275751,"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."}}