{"id":"W2486953319","doi":"10.1109/icecs.2001.957479","title":"Fast 32-bit digital multiplier","year":2002,"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; Toronto Metropolitan University","funders":"","keywords":"Multiplier (economics); Adder; Arithmetic; 4-bit; Bit (key); Very-large-scale integration; 8-bit; Carry (investment); Pairwise comparison; Computer science; 16-bit; Propagation delay; Voltage; Mathematics; Electronic engineering; Computer hardware; Electrical engineering; CMOS; Engineering; Statistics","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":[0.00002402863,0.0001491838,0.0001132843,0.00007143283,0.0000336422,0.00008970562,0.0001442837,0.00006377936,0.002067071],"category_scores_gemma":[0.00000693458,0.0001315313,0.00004406618,0.0001513172,0.0000221977,0.000497679,0.00002406376,0.0001131105,0.007072768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004166966,"about_ca_system_score_gemma":0.000001669845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001578296,"about_ca_topic_score_gemma":0.000001644587,"domain_scores_codex":[0.9992811,0.000002139184,0.0001491572,0.0001324437,0.0001407264,0.000294421],"domain_scores_gemma":[0.999631,0.00002046791,0.00000832689,0.0002395886,0.00001485619,0.00008572762],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001245602,0.0003004878,0.01507325,0.0002008333,0.0002864514,0.0001094939,0.003141305,0.07314379,0.01649597,0.001547889,0.5229157,0.3667724],"study_design_scores_gemma":[0.001081979,0.00006506738,0.002548541,0.00002622856,0.0000132587,0.00002967511,0.0001076156,0.7521549,0.01772784,0.00005089165,0.2253534,0.0008404918],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2899812,0.0002707933,0.01886225,0.00008093534,0.000772682,0.0002115957,0.00001480709,0.001968762,0.6878369],"genre_scores_gemma":[0.9862273,0.00002742466,0.001072458,0.00004928299,0.0001160723,0.00001037837,0.000003902236,0.00004360515,0.01244961],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.696246,"threshold_uncertainty_score":0.9988452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007864621367539293,"score_gpt":0.1501607320666969,"score_spread":0.1422961106991576,"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."}}