{"id":"W2965766329","doi":"10.1109/aicas.2019.8771594","title":"Memristor Emulators for an Adaptive DPE Algorithm: Comparative Study","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Institut de Valorisation des Données","keywords":"Memristor; Computer science; Matrix multiplication; Resistive random-access memory; Process (computing); Dot product; Algorithm; Resistive touchscreen; Multiplication (music); Electronic engineering; Voltage; Engineering; Electrical engineering; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006526249,0.0001336201,0.0002004501,0.00003617297,0.00005645814,0.00001103769,0.00009575938,0.00002590892,0.00003570548],"category_scores_gemma":[0.000002201654,0.0001201097,0.00003669133,0.00007881999,0.000007972676,0.0002096011,0.00001773732,0.00009404968,0.00004810568],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003770155,"about_ca_system_score_gemma":0.00000432366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002806232,"about_ca_topic_score_gemma":0.00001033437,"domain_scores_codex":[0.9994051,0.00001746853,0.0001352563,0.0001873826,0.00007445839,0.0001802983],"domain_scores_gemma":[0.9996442,0.00008524703,0.00001878624,0.0001543141,0.00003538438,0.00006212437],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003334097,0.0005526305,0.000985923,0.00007549428,0.0003516409,0.00001007909,0.01446106,0.9059258,0.02318931,0.001879963,0.001570671,0.05066406],"study_design_scores_gemma":[0.001242103,0.002314737,0.000624501,0.000009815039,0.00001966153,0.000002268714,0.007765214,0.9609303,0.02491519,0.0002746579,0.001501506,0.000400056],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8940375,0.0000295979,0.1016129,0.000001592491,0.000434059,0.0008186502,0.000005122077,0.0003400463,0.002720568],"genre_scores_gemma":[0.9877203,3.887101e-7,0.01167513,0.00001796515,0.00008964045,0.00002087423,0.000003505889,0.00002057641,0.0004516155],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0936828,"threshold_uncertainty_score":0.4897932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05642397874656165,"score_gpt":0.3075117528349413,"score_spread":0.2510877740883796,"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."}}