{"id":"W4389209482","doi":"10.1016/j.mtnano.2023.100439","title":"Research progress of artificial neural systems based on memristors","year":2023,"lang":"en","type":"article","venue":"Materials Today Nano","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Xi’an Jiaotong University; National Natural Science Foundation of China","keywords":"Memristor; Artificial neural network; Computer science; Artificial intelligence; Process (computing); Neural system; Engineering; Control engineering; Electronic engineering; Neuroscience","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":[0.0007478528,0.0001186948,0.0002282582,0.0002341847,0.00009473305,0.00004162372,0.0001535116,0.00006618554,0.00003949392],"category_scores_gemma":[0.00004521031,0.0001076988,0.00003051434,0.0004572073,0.00005554069,0.00005248431,0.00003730601,0.00009849345,0.0001063037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003789573,"about_ca_system_score_gemma":0.00001106398,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006197322,"about_ca_topic_score_gemma":5.360057e-7,"domain_scores_codex":[0.9987236,0.0001440679,0.0003116639,0.000171188,0.000291321,0.0003581882],"domain_scores_gemma":[0.9994811,0.0001482407,0.00003829738,0.0002331191,0.00005119765,0.0000480178],"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":[0.00005725419,0.00001281189,0.00001612114,0.0002884389,0.000004546879,0.0000273595,0.00005546721,0.1620622,0.8356671,0.0002084397,0.0006230042,0.0009772637],"study_design_scores_gemma":[0.0001168443,0.0001022859,0.0001555804,0.000118739,0.00000283074,0.000001455306,0.0000493855,0.03334864,0.9651614,0.00005207449,0.0007725669,0.0001181564],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965635,0.00004466997,0.00005091208,0.00003106268,0.002344862,0.0002620889,0.00002495845,0.0004450805,0.0002328714],"genre_scores_gemma":[0.9994822,0.000002598548,0.00003904406,0.000004799022,0.0002878494,0.00003739648,0.00001669249,0.00003736628,0.0000920128],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1294944,"threshold_uncertainty_score":0.4391828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06079025923780432,"score_gpt":0.3215654114013894,"score_spread":0.260775152163585,"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."}}