{"id":"W2461274627","doi":"10.1109/tc.2015.2493547","title":"Approximate Radix-8 Booth Multipliers for Low-Power and High-Performance Operation","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Computers","topic":"Low-power high-performance VLSI design","field":"Engineering","cited_by":221,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Adder; Arithmetic; Multiplier (economics); Notation; Mathematics; Binary number; Carry-save adder; Multiplication (music); Discrete mathematics; Computer science; Combinatorics","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":[0.0001782831,0.0002827989,0.0002429921,0.0002175895,0.0001680837,0.00009580483,0.0001644447,0.000117353,0.000009143695],"category_scores_gemma":[0.00000139256,0.0002851623,0.00005451112,0.0001738373,0.00006639437,0.0005560637,0.000001479861,0.0002025334,0.0000491446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001680438,"about_ca_system_score_gemma":0.00003374692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007391779,"about_ca_topic_score_gemma":0.000003665339,"domain_scores_codex":[0.9988396,0.00001823153,0.0002756379,0.0003010285,0.0001985175,0.0003670036],"domain_scores_gemma":[0.9993687,0.00006552469,0.00002980227,0.000280604,0.0000579504,0.0001973975],"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":[0.00008056244,0.0000528209,0.00001168993,0.00008595295,0.00006933916,0.00000150477,0.0008018778,0.9724347,0.001790224,0.0000269729,0.001686097,0.02295826],"study_design_scores_gemma":[0.002059251,0.0002807669,0.00007547508,0.00006170924,0.000026714,0.00001116975,0.00004609894,0.9390372,0.05706799,0.00001055675,0.0009559009,0.0003671813],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2994923,0.00003288333,0.6971866,0.00004442516,0.002278147,0.0004493233,0.00002000368,0.0004106347,0.00008567513],"genre_scores_gemma":[0.9765074,0.00007035591,0.02295115,0.0001099586,0.00007570132,0.0001400445,0.000008463431,0.00007162429,0.00006535022],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.677015,"threshold_uncertainty_score":0.9999601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01258042604090034,"score_gpt":0.2015053349789125,"score_spread":0.1889249089380122,"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."}}