{"id":"W6991342587","doi":"","title":"Fuzzy wavelet packet based feature extraction method and its application to biomedical classification","year":2005,"lang":"en","type":"article","venue":"NPARC","topic":"Health, Technology, Consumer Behavior","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pattern recognition (psychology); Feature extraction; Fuzzy logic; Feature (linguistics); Wavelet; Wavelet packet decomposition","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005594507,0.0002510862,0.0004621599,0.0008636354,0.000245221,0.0004075601,0.0002797158,0.0004782184,0.002155598],"category_scores_gemma":[0.001393669,0.0001712174,0.0004011306,0.001252116,0.0001875948,0.0003597478,0.0001720703,0.0004535924,0.0006574431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001438664,"about_ca_system_score_gemma":0.0002722844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00133402,"about_ca_topic_score_gemma":0.0009130904,"domain_scores_codex":[0.999885,0.00001916623,0.00001216078,0.00001863141,0.00005455084,0.00001051309],"domain_scores_gemma":[0.9994992,0.0002087164,0.00002178817,0.00003990479,0.0002170675,0.00001330426],"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":[0.000328699,0.0001202922,0.0009781438,0.0001927944,0.0000456273,0.0001453831,0.00007118593,0.0108879,0.09793222,0.003044342,0.00365591,0.8825975],"study_design_scores_gemma":[0.00006244791,0.0004372056,0.0121072,0.00006064111,0.0001800124,0.0007978025,0.00007179668,0.8646668,0.1072366,0.002785693,0.01152402,0.00006982531],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02963983,0.0004614965,0.9676439,0.0001526896,0.0001606808,0.00006979746,0.0001688916,0.000488267,0.00121452],"genre_scores_gemma":[0.2584921,0.001316991,0.7333906,0.000103371,0.000148572,0.0001924132,0.0004198532,0.00008282551,0.005853341],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002155598,"threshold_uncertainty_score":0.007211208,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07454153684272267,"score_gpt":0.4665506870041634,"score_spread":0.3920091501614407,"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."}}