{"id":"W2798000764","doi":"10.1109/tvlsi.2018.2818980","title":"Approximate Sum-of-Products Designs Based on Distributed Arithmetic","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Very Large Scale Integration (VLSI) Systems","topic":"Low-power high-performance VLSI design","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; University of Saskatchewan","keywords":"Computer science; Smoothing; Power (physics); Algorithm; Approximation error; Key (lock); Signal-to-noise ratio (imaging); Word error rate; Arithmetic; Mathematics; Artificial intelligence; Telecommunications","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":[0.0004274258,0.0006713783,0.0006795262,0.0005032466,0.0003928757,0.001150536,0.001555407,0.0006023776,0.002969047],"category_scores_gemma":[0.001148089,0.0002898128,0.0004666959,0.0007685064,0.0004651698,0.001772989,0.000465355,0.0007082394,0.0007228016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006871707,"about_ca_system_score_gemma":0.0007408031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000747687,"about_ca_topic_score_gemma":0.001350276,"domain_scores_codex":[0.9994426,0.000100176,0.00004155142,0.0001019207,0.0002692541,0.00004435206],"domain_scores_gemma":[0.9995549,0.0001191734,0.0000616777,0.0001205178,0.000127777,0.00001595788],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000592839,0.0001408063,0.001095766,0.0007324953,0.0001868037,0.0002608631,0.0002283488,0.3074446,0.09078769,0.1741313,0.006646711,0.4177518],"study_design_scores_gemma":[0.00006027578,0.0006913721,0.0003062572,0.00004598051,0.0001239874,0.0005163699,0.00003901679,0.8985128,0.04823133,0.02563303,0.02579912,0.00004042647],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02755701,0.001352105,0.96124,0.0001278969,0.0001191255,0.00008494375,0.0001144112,0.0009904178,0.008414197],"genre_scores_gemma":[0.57454,0.001289294,0.4176498,0.0001768371,0.0001178349,0.0001920237,0.0002333257,0.0000905824,0.00571024],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002969047,"threshold_uncertainty_score":0.009932458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01770565476988376,"score_gpt":0.2232772957593894,"score_spread":0.2055716409895057,"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."}}