{"id":"W2161010017","doi":"10.1109/coginf.2003.1225951","title":"Signal classification through multifractal analysis and complex domain neural networks","year":2004,"lang":"en","type":"article","venue":"","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Multifractal system; Pattern recognition (psychology); Computer science; Artificial intelligence; Artificial neural network; Affine transformation; Probabilistic logic; Fractal; Probabilistic neural network; Self-organizing map; SIGNAL (programming language); Domain (mathematical analysis); Dimension (graph theory); Feature extraction; Contextual image classification; Feature (linguistics); Time delay neural network; Mathematics; Image (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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001070049,0.0004983161,0.0003992616,0.001456028,0.0003542312,0.0009804519,0.000443708,0.0008308879,0.0009539934],"category_scores_gemma":[0.003324021,0.0001881299,0.0004355629,0.001120373,0.0006716739,0.001447135,0.0004062182,0.0006529936,0.0003379051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006453072,"about_ca_system_score_gemma":0.0003324277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003166786,"about_ca_topic_score_gemma":0.002815807,"domain_scores_codex":[0.9994366,0.0001674756,0.00003555182,0.00009956254,0.0002153328,0.00004563398],"domain_scores_gemma":[0.9991469,0.0004700773,0.0001177028,0.00007325266,0.0001758987,0.00001608423],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001808756,0.0001140961,0.003157755,0.0001629787,0.000106341,0.0001371488,0.0001801196,0.3619756,0.02617343,0.03926836,0.002014309,0.5665289],"study_design_scores_gemma":[0.000003473443,0.00001696937,0.0006526652,0.00001037303,0.00000796881,0.00003411259,0.00001196677,0.9872415,0.002661801,0.008290291,0.001059174,0.000009658219],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02649352,0.001089256,0.9695721,0.0003247004,0.00006156941,0.00004208603,0.00005618022,0.0005268257,0.001833694],"genre_scores_gemma":[0.4544515,0.00105297,0.5410687,0.0001659874,0.0001574531,0.000105948,0.0001815627,0.00007085323,0.002745091],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003166786,"threshold_uncertainty_score":0.006296694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03364316341323907,"score_gpt":0.2745696509863145,"score_spread":0.2409264875730754,"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."}}