{"id":"W2887090061","doi":"10.1109/mnano.2018.2845078","title":"Building Brain-Inspired Computing Systems: Examining the Role of Nanoscale Devices","year":2018,"lang":"en","type":"article","venue":"IEEE Nanotechnology Magazine","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institute for Advanced Research; Cisco Systems; National Science Foundation","keywords":"Computer science; Realization (probability); Variety (cybernetics); State (computer science); Memristor; Distributed computing; Process (computing); Parallelism (grammar); Reservoir computing; Computer architecture; Artificial intelligence; Electronic engineering; Artificial neural network; Parallel computing","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":[0.000309002,0.0002742038,0.0003468341,0.0003167312,0.0005743176,0.001828236,0.0008868809,0.001228754,0.002247187],"category_scores_gemma":[0.0009450615,0.0002688084,0.0002295962,0.0002219052,0.001944798,0.003187999,0.0008648324,0.001146124,0.0007234825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006228639,"about_ca_system_score_gemma":0.0005150052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005970877,"about_ca_topic_score_gemma":0.0007234697,"domain_scores_codex":[0.9998773,0.00002409086,0.00000310447,0.00002023931,0.00005008933,0.00002519848],"domain_scores_gemma":[0.9998341,0.00007884694,0.00001365249,0.00002346246,0.00002694309,0.00002294927],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008307334,0.0001203341,0.001137692,0.00122761,0.00005153957,0.0002646715,0.0005683503,0.04215933,0.06607296,0.7687244,0.0098412,0.1097488],"study_design_scores_gemma":[0.00005079221,0.000261217,0.001488105,0.0003744099,0.00005116607,0.0003120126,0.0005897849,0.1876363,0.04252,0.5994051,0.1672448,0.00006642519],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3416311,0.1523244,0.2362873,0.02659839,0.00223479,0.0002476042,0.0002720141,0.001569999,0.2388344],"genre_scores_gemma":[0.8786935,0.04545431,0.06368279,0.001386031,0.00034922,0.0001772107,0.0001042389,0.0001689873,0.009983761],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002247187,"threshold_uncertainty_score":0.007517576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01386937274854234,"score_gpt":0.2419700463461583,"score_spread":0.2281006735976159,"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."}}