{"id":"W4400222598","doi":"10.48550/arxiv.2406.19667","title":"Versatile CMOS Analog LIF Neuron for Memristor-Integrated Neuromorphic Circuits","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"CMC Microsystems","keywords":"Neuromorphic engineering; Memristor; CMOS; Analogue electronics; Electronic circuit; Computer science; Electronic engineering; Computer architecture; Memistor; Electrical engineering; Resistive random-access memory; Artificial intelligence; Voltage; Engineering; Artificial neural network","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0001011985,0.0001959094,0.0001754599,0.0001582458,0.0002671204,0.0004109972,0.0007363422,0.0004101369,0.001695514],"category_scores_gemma":[0.0001534807,0.00009510924,0.0001579455,0.000151374,0.0002244818,0.0004325839,0.0003341617,0.0003231206,0.0003652765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003832094,"about_ca_system_score_gemma":0.0001614026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002443027,"about_ca_topic_score_gemma":0.0005824061,"domain_scores_codex":[0.9999241,0.000008256535,0.000004257052,0.00001911156,0.00003269549,0.00001162483],"domain_scores_gemma":[0.9999657,0.000006077768,0.000006086846,0.000006224457,0.00001062634,0.000005353856],"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":[0.0001282685,0.00005836671,0.0005173724,0.0002186049,0.00002420026,0.000274295,0.000102978,0.006356403,0.8987476,0.02197538,0.001233124,0.07036337],"study_design_scores_gemma":[0.0000680748,0.0003884014,0.001213455,0.00008275704,0.00007387688,0.00108293,0.00006397756,0.220536,0.7122812,0.0108886,0.05327822,0.00004245792],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2512884,0.004191666,0.7110788,0.0008327503,0.0003421586,0.0001427314,0.0002590447,0.00281607,0.02904845],"genre_scores_gemma":[0.8699058,0.0005942102,0.1222553,0.00025276,0.0000372568,0.00005949788,0.00006183291,0.00003999198,0.006793294],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001695514,"threshold_uncertainty_score":0.005672038,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09446519308435226,"score_gpt":0.1862195328679624,"score_spread":0.09175433978361015,"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."}}