{"id":"W2140587552","doi":"10.1109/ccece.1999.807254","title":"Fast carry-look-ahead adder","year":2003,"lang":"en","type":"article","venue":"","topic":"Low-power high-performance VLSI design","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Adder; Carry (investment); Carry-save adder; Serial binary adder; Computer science; Very-large-scale integration; Arithmetic; Parallel computing; Look-ahead; Computer hardware; Electronic engineering; Engineering; Embedded system; Mathematics; Telecommunications; Algorithm; Latency (audio)","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00009633252,0.0001676692,0.0001410191,0.00008199484,0.00004328193,0.00003213434,0.0001207369,0.00008303775,0.001649362],"category_scores_gemma":[0.00001141921,0.0001502011,0.000044853,0.0001946092,0.00002197211,0.0001983997,0.000009546708,0.0001401553,0.001435142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005119956,"about_ca_system_score_gemma":0.0000179666,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009333997,"about_ca_topic_score_gemma":0.00001506273,"domain_scores_codex":[0.9991698,0.00001303536,0.0001638693,0.000150347,0.000151749,0.0003511512],"domain_scores_gemma":[0.999548,0.00002027982,0.000009293017,0.0003009933,0.00002430193,0.000097155],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002183036,0.0002222111,0.02222757,0.0004750484,0.0005557116,0.000142369,0.004093882,0.1294032,0.08708758,0.0763062,0.6393293,0.04013513],"study_design_scores_gemma":[0.001991371,0.0001396914,0.003850953,0.00006187631,0.00006153881,0.00008582724,0.0006579239,0.04011068,0.3262733,0.0006089654,0.624386,0.00177192],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2626922,0.0005230249,0.02778816,0.000044922,0.001399603,0.0002380112,0.000005201798,0.001361993,0.7059469],"genre_scores_gemma":[0.9898131,0.00002880745,0.003720611,0.0001093902,0.00007474019,0.00001776677,0.000002887814,0.00005271918,0.006179979],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7271209,"threshold_uncertainty_score":0.9993424,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007167364740959977,"score_gpt":0.1851375152512036,"score_spread":0.1779701505102436,"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."}}