{"id":"W4301343525","doi":"10.48550/arxiv.1001.5272","title":"An in-place truncated Fourier transform and applications to polynomial\\n multiplication","year":2010,"lang":"","type":"preprint","venue":"arXiv (Cornell University)","topic":"Polynomial and algebraic computation","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Fast Fourier transform; Multiplication (music); Split-radix FFT algorithm; Smoothing; Inverse; Polynomial; Arithmetic; Prime-factor FFT algorithm; Fourier transform; Mathematics; Rader's FFT algorithm; Discrete Fourier transform (general); Algorithm; Computer science; Discrete mathematics; Combinatorics; Mathematical analysis; Short-time Fourier transform; Fourier analysis; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006701439,0.0009258156,0.0007154625,0.0008008765,0.0007113714,0.001351454,0.001022452,0.0008260282,0.009198773],"category_scores_gemma":[0.004775218,0.0003664775,0.000777459,0.001391775,0.001578336,0.002104827,0.002007752,0.002510729,0.003261653],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000693461,"about_ca_system_score_gemma":0.0005388072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008210752,"about_ca_topic_score_gemma":0.0009579851,"domain_scores_codex":[0.9992304,0.0001768195,0.00005064277,0.0001205087,0.0003318874,0.00008978422],"domain_scores_gemma":[0.9987669,0.0004821621,0.00007006938,0.0004364962,0.0001879329,0.00005640939],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004477544,0.0001462213,0.0005775229,0.000319571,0.00003717631,0.0004760819,0.000446689,0.04405132,0.04561378,0.4755645,0.01011351,0.4222058],"study_design_scores_gemma":[0.00006422641,0.0002377397,0.0003286297,0.0000766204,0.00003685284,0.001550699,0.00009995615,0.4831306,0.07718164,0.3706342,0.06659263,0.00006610631],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009759332,0.000559147,0.9798306,0.0002975638,0.00020852,0.00002811985,0.00005476923,0.0007269087,0.008534969],"genre_scores_gemma":[0.2474125,0.001844791,0.7344904,0.0002692897,0.0005849947,0.00008573273,0.0002791518,0.0007478384,0.01428535],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009198773,"threshold_uncertainty_score":0.03077298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03470318859741409,"score_gpt":0.2049086806593006,"score_spread":0.1702054920618865,"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."}}