{"id":"W4387831750","doi":"10.1109/tnano.2023.3326199","title":"A Survey of Majority Logic Designs in Emerging Nanotechnologies for Computing","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Nanotechnology","topic":"Quantum-Dot Cellular Automata","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Logic gate; Computer science; CMOS; Logic synthesis; Logic family; Pass transistor logic; Theoretical computer science; Computer architecture; Electronic circuit; Electronic engineering; Digital electronics; 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":[0.001199021,0.0002374914,0.0004604289,0.001647714,0.0001844244,0.00002626256,0.001544208,0.0005057878,0.000003847555],"category_scores_gemma":[0.0001713516,0.0002504873,0.0001201308,0.004017817,0.0002219281,0.0001748871,0.00003087888,0.0004753136,0.00004384874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009684619,"about_ca_system_score_gemma":0.0001042912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002837176,"about_ca_topic_score_gemma":0.0005569482,"domain_scores_codex":[0.9977653,0.0001534679,0.0005759343,0.0006593537,0.0002116648,0.0006342611],"domain_scores_gemma":[0.9978011,0.0008604798,0.0001834424,0.001002792,0.0001203078,0.00003191174],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001431558,0.0009917708,0.0006880104,0.0003332242,0.0001841242,0.0001687231,0.0009606538,0.08987185,0.2458275,0.04955368,0.0002788126,0.6109985],"study_design_scores_gemma":[0.0008086091,0.0003822801,0.001040217,0.0000638857,0.00000933601,0.00001810695,0.00009175466,0.5017391,0.484582,0.01087786,0.00006661879,0.0003202268],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2236712,0.0000534926,0.7724234,0.001098567,0.000524033,0.0004035192,0.00002420998,0.001796213,0.000005252513],"genre_scores_gemma":[0.97824,0.00005522856,0.0215379,0.0000375397,0.000003585727,0.00006957919,0.000004121064,0.00002288479,0.00002917999],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7545688,"threshold_uncertainty_score":0.9999948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0784320334932822,"score_gpt":0.3094082856687457,"score_spread":0.2309762521754635,"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."}}