{"id":"W1975047642","doi":"10.1109/iscas.2010.5537705","title":"Recursive architectures for 2DLNS multiplication","year":2010,"lang":"en","type":"article","venue":"","topic":"Low-power high-performance VLSI design","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada; University of Windsor; CMC Microsystems","keywords":"Multiplication (music); Computer science; Digital signal processing; Flexibility (engineering); Recursion (computer science); Electronic circuit; Implementation; Electronic engineering; Computer hardware; Algorithm; Engineering; Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.00006723405,0.00009641815,0.00007599541,0.00006705858,0.00004191692,0.00001709374,0.0001287832,0.0000720667,0.00008130525],"category_scores_gemma":[0.00003433619,0.00008296392,0.00003668108,0.00007480002,0.00002005444,0.00003552688,0.000008103745,0.0001424333,0.00009600745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001378077,"about_ca_system_score_gemma":0.000007076068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004865075,"about_ca_topic_score_gemma":0.00004605146,"domain_scores_codex":[0.9995345,0.000002701865,0.0001028048,0.0001150038,0.00006293772,0.0001820833],"domain_scores_gemma":[0.9996038,0.00007058464,0.00001245106,0.0002295794,0.00003392385,0.00004964549],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004074787,0.00005807177,0.001329019,0.0001632351,0.00008762845,0.000001418057,0.001756252,0.03200355,0.8056713,0.01119701,0.0329366,0.1147551],"study_design_scores_gemma":[0.0009111743,0.00008551119,0.008064803,0.00001256975,0.00002173448,0.0000156728,0.00004593311,0.2055272,0.699498,0.003846021,0.08146336,0.0005080337],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8779328,0.00002582589,0.1094893,0.0001702266,0.0008482701,0.0005400777,0.00001148269,0.0006899385,0.01029196],"genre_scores_gemma":[0.9621681,0.000002842121,0.03707081,0.00004228771,0.0002089652,0.0001311868,0.000009110633,0.0000299304,0.0003367765],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1735236,"threshold_uncertainty_score":0.3383171,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005510414312484865,"score_gpt":0.2125314080942984,"score_spread":0.2070209937818136,"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."}}