{"id":"W2139250652","doi":"10.1109/icassp.1983.1172001","title":"Non-recursive digital FIR filter implementation using stored square ROM multipliers","year":2005,"lang":"en","type":"article","venue":"","topic":"Digital Filter Design and Implementation","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Multiplier (economics); Finite impulse response; Digital filter; Realization (probability); Computer science; Arithmetic; Square (algebra); Digital signal processing; Filter (signal processing); Mathematics; Algorithm; Computer hardware; 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":[],"consensus_categories":[],"category_scores_codex":[0.00007587689,0.0001713625,0.0001204752,0.0001317342,0.0001172929,0.0007826256,0.0003972157,0.0000335928,0.0001847616],"category_scores_gemma":[0.000006927099,0.000163122,0.00007849497,0.0002462824,0.00002227849,0.00457856,0.0001528066,0.00005410942,0.0001717476],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001660282,"about_ca_system_score_gemma":0.00005918369,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000049328,"about_ca_topic_score_gemma":0.00004815133,"domain_scores_codex":[0.9986645,0.00001408718,0.0003050738,0.0003687605,0.0003007448,0.0003468294],"domain_scores_gemma":[0.9993606,0.00003398968,0.0001041415,0.0002983714,0.00008533725,0.0001175262],"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":[0.00002746186,0.0002104243,0.006847922,0.00002111715,0.00009121005,0.00001242502,0.006610688,0.0007565001,0.01552098,0.008744406,0.02811703,0.9330398],"study_design_scores_gemma":[0.01279226,0.001672091,0.09181222,0.0001345261,0.00008382706,0.000126618,0.01112059,0.6053649,0.1664667,0.00820469,0.09841508,0.003806448],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2483033,0.000008413459,0.7457101,0.0005209027,0.0002527535,0.000440531,0.00004536627,0.0001601938,0.004558439],"genre_scores_gemma":[0.9371435,8.821294e-7,0.06161894,0.0005745128,0.0001019731,0.00001429003,0.0001030092,0.00001284268,0.000430064],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9292334,"threshold_uncertainty_score":0.7546877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03131555419467738,"score_gpt":0.305008061821383,"score_spread":0.2736925076267056,"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."}}