{"id":"W3159146981","doi":"10.1021/acsaelm.1c00271","title":"A True Random Number Generator Based on Ionic Liquid Modulated Memristors","year":2021,"lang":"en","type":"article","venue":"ACS Applied Electronic Materials","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Department of Science and Technology of Sichuan Province; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Memristor; Ionic liquid; Neuromorphic engineering; Materials science; Nanotechnology; Computer science; Ultrashort pulse; Topology (electrical circuits); Artificial neural network; Electronic engineering; Electrical engineering; Artificial intelligence; Chemistry; Physics; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002205664,0.0002770176,0.0002683278,0.000238607,0.0001901329,0.0003545479,0.0006146667,0.0004261684,0.001316125],"category_scores_gemma":[0.0005290463,0.0001844941,0.0001947444,0.0001962414,0.0003090367,0.0005925013,0.0002654987,0.0002993953,0.0004266782],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002431695,"about_ca_system_score_gemma":0.0002051258,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000132329,"about_ca_topic_score_gemma":0.0001406942,"domain_scores_codex":[0.9997831,0.00005491802,0.00001352028,0.00005388386,0.00006741697,0.00002722287],"domain_scores_gemma":[0.9997957,0.00006482359,0.00005029757,0.00002328607,0.00004455944,0.00002124911],"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":[0.0003939098,0.0001662124,0.0009634134,0.0002737581,0.00004585418,0.0008975056,0.0001152807,0.02369902,0.8794601,0.03350371,0.002216499,0.05826478],"study_design_scores_gemma":[0.000127155,0.0006629225,0.0005490186,0.00002436538,0.0000349595,0.000707882,0.0000157283,0.5301962,0.4555843,0.003482504,0.008535696,0.00007918499],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3467108,0.001183708,0.6313392,0.001159646,0.0006016887,0.0003678369,0.0002814838,0.003315728,0.01503982],"genre_scores_gemma":[0.9307607,0.0002305922,0.0653199,0.0001599252,0.00003223934,0.0001100123,0.00005259394,0.0000537559,0.003280177],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001316125,"threshold_uncertainty_score":0.004402876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005742239491315662,"score_gpt":0.2076659335809522,"score_spread":0.2019236940896365,"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."}}