{"id":"W2774047826","doi":"10.1109/nano.2017.8117301","title":"An area-efficient ternary full adder using hybrid SET-MOS technology","year":2017,"lang":"en","type":"article","venue":"","topic":"Low-power high-performance VLSI design","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Adder; CMOS; Ternary operation; Computer science; Cadence; Transistor; Electronic engineering; Set (abstract data type); Electrical engineering; Voltage; Engineering","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":[0.0001146921,0.0002336779,0.000208256,0.0002330655,0.0002800399,0.0001321571,0.000684955,0.0001211246,0.0003088826],"category_scores_gemma":[0.00001437629,0.0002128887,0.00004277188,0.00008782333,0.0001091757,0.0003461307,0.0001062563,0.0002248331,0.0002423051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009696472,"about_ca_system_score_gemma":0.00002400225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003184285,"about_ca_topic_score_gemma":0.00001020494,"domain_scores_codex":[0.9988605,0.000007890932,0.0002156172,0.0002802026,0.0001702284,0.0004655239],"domain_scores_gemma":[0.9985785,0.000009585057,0.00005320621,0.001214543,0.0000415464,0.0001026548],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004696065,0.0002457126,0.01445835,0.0001496211,0.0002798069,0.0005365638,0.0004860676,0.4272139,0.5203212,0.0009833743,0.008866603,0.02641187],"study_design_scores_gemma":[0.0003356072,0.00007215008,0.0008532997,0.00003329018,0.00002084074,0.0001233939,0.00006878105,0.9112319,0.08490219,0.00005588388,0.001948955,0.0003536996],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9343808,0.00009847378,0.05844241,0.00007214923,0.0007369109,0.0001914618,0.00001159253,0.001027116,0.005039109],"genre_scores_gemma":[0.9941928,0.00001296529,0.005405257,0.00003331385,0.0001236332,0.00001441445,0.000005525066,0.00006236225,0.0001496752],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.484018,"threshold_uncertainty_score":0.868135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02151469099334653,"score_gpt":0.2526096397944068,"score_spread":0.2310949488010603,"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."}}