{"id":"W4416252542","doi":"10.1002/cta.70211","title":"VLPPLAs: Variable Latency Parallel Prefix Ling Adders","year":2025,"lang":"en","type":"article","venue":"International Journal of Circuit Theory and Applications","topic":"Low-power high-performance VLSI design","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Fundamental Research Funds for the Central Universities; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Adder; Operand; Latency (audio); Prefix; Cyclic prefix; Variable (mathematics); Error detection and correction","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":[0.0002423684,0.0003685608,0.0002107496,0.000604154,0.000324776,0.0007638842,0.001044859,0.0002254559,0.003244008],"category_scores_gemma":[0.000517859,0.0002229348,0.0002042288,0.0006267802,0.0002943487,0.000957444,0.0004624744,0.0003824264,0.0005615539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000400574,"about_ca_system_score_gemma":0.0008581742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008228904,"about_ca_topic_score_gemma":0.001836738,"domain_scores_codex":[0.9998246,0.00003110721,0.00002112791,0.00003550543,0.00006125937,0.00002648816],"domain_scores_gemma":[0.9996766,0.00006109827,0.0000983884,0.00005773909,0.00008555522,0.00002060314],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001435072,0.0001515104,0.002909871,0.0006577394,0.0001671685,0.0008119817,0.0001512084,0.1068087,0.2687941,0.03513839,0.01173936,0.5712349],"study_design_scores_gemma":[0.0002324003,0.002523681,0.002549366,0.0001287796,0.0003188117,0.002033037,0.00012263,0.4943166,0.4150958,0.01910206,0.06342486,0.000152081],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2338532,0.003078199,0.7383513,0.0003733931,0.0003265874,0.0002056738,0.0006473057,0.01009803,0.01306629],"genre_scores_gemma":[0.8213968,0.0007920076,0.1701834,0.0002863218,0.0000779264,0.000100578,0.00049167,0.00009144328,0.006579668],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003244008,"threshold_uncertainty_score":0.01085228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005220761463879296,"score_gpt":0.2247985398895764,"score_spread":0.2195777784256971,"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."}}