{"id":"W1587360322","doi":"10.1023/a:1022236132192","title":"Fast Fourier Transforms Using the Complex Logarithmic Number System","year":2003,"lang":"en","type":"article","venue":"The Journal of VLSI Signal Processing Systems for Signal Image and Video Technology","topic":"Numerical Methods and Algorithms","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Ryerson University","keywords":"Logarithm; Fast Fourier transform; Arithmetic; Computer science; Point (geometry); Algorithm; Adder; Multiplication (music); Mathematics; Geometry; Telecommunications; Combinatorics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003648296,0.00029456,0.000618434,0.0002014615,0.0008354636,0.0003938298,0.001183246,0.0001780661,0.000005083529],"category_scores_gemma":[0.00006799454,0.0001497127,0.0001606151,0.0007591275,0.0004678698,0.0006526276,0.00008376161,0.0005671256,0.000002392125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000795286,"about_ca_system_score_gemma":0.0001804601,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002261526,"about_ca_topic_score_gemma":5.789144e-7,"domain_scores_codex":[0.9974191,0.000471184,0.0008991279,0.0002677897,0.0004208872,0.0005219457],"domain_scores_gemma":[0.997705,0.0004758588,0.0008247868,0.0003097605,0.0005745556,0.0001100462],"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":[0.0002304537,0.0002858221,0.0002388392,0.001618825,0.000558057,0.0001962468,0.00243062,0.00155763,0.2403753,0.06787271,0.0007945967,0.6838409],"study_design_scores_gemma":[0.002572853,0.001229789,0.00002316037,0.001405153,0.0004423056,0.02816281,0.008641158,0.8928662,0.02456462,0.02872061,0.01054215,0.0008292188],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004817691,0.002971279,0.9903384,0.0009411137,0.0002383414,0.0004411091,0.000004249951,0.00008209731,0.000165745],"genre_scores_gemma":[0.8375643,0.00003018495,0.1620185,0.0001033437,0.0001900638,0.00001589635,1.976769e-7,0.00002823688,0.00004922945],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8913085,"threshold_uncertainty_score":0.6425795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02984980384153831,"score_gpt":0.3035803363279219,"score_spread":0.2737305324863836,"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."}}