{"id":"W4295935088","doi":"10.1109/jxcdc.2022.3206778","title":"Scalable 2T2R Logic Computation Structure: Design From Digital Logic Circuits to 3-D Stacked Memory Arrays","year":2022,"lang":"en","type":"article","venue":"IEEE Journal on Exploratory Solid-State Computational Devices and Circuits","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; University of Waterloo; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"XNOR gate; Computer science; Logic gate; Digital electronics; Resistive random-access memory; Semiconductor memory; CMOS; Sense amplifier; Scalability; Electronic circuit; Pass transistor logic; Computer architecture; Parallel computing; NAND gate; Computer hardware; Electronic engineering; Engineering; Electrical engineering; Algorithm","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000315135,0.0004555264,0.0004781233,0.0003280086,0.0009775406,0.0004148367,0.0003314138,0.00006594765,0.00007283119],"category_scores_gemma":[0.00003173775,0.0004714173,0.0001051544,0.0005113317,0.0000534051,0.0009219645,0.00007685166,0.0008026832,0.00004620519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002838107,"about_ca_system_score_gemma":0.0001106756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.202801e-7,"about_ca_topic_score_gemma":0.000001314002,"domain_scores_codex":[0.9971954,0.0002430692,0.0007200085,0.000518941,0.0007793506,0.0005432497],"domain_scores_gemma":[0.9983818,0.0005390719,0.0002737411,0.0001486574,0.0002205091,0.0004362321],"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":[0.00003736377,0.00005196247,0.00004523358,0.00003092837,0.00008693514,0.0001716323,0.001129419,0.9722216,0.005475035,0.00005347294,0.0007087959,0.01998763],"study_design_scores_gemma":[0.004059732,0.001977787,0.003512156,0.0003231856,0.0001163826,0.0009229131,0.002985772,0.795913,0.009556464,0.1754979,0.0024057,0.002728911],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5841984,0.0005503944,0.412857,0.000105729,0.001433089,0.0003171275,0.0002321461,0.0002133051,0.0000928197],"genre_scores_gemma":[0.996451,0.00003096653,0.001064928,0.00183133,0.0003910304,0.00002121863,0.0001075192,0.00007944946,0.00002257022],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4122526,"threshold_uncertainty_score":0.9997737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04175348740880933,"score_gpt":0.2616967595165738,"score_spread":0.2199432721077645,"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."}}