{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0013917,0.0001678923,0.0002367009,0.0002949458,0.0004743222,0.000007384097,0.0001716372,0.0008628333,0.000286909],"category_scores_gemma":[0.0004206969,0.0001598924,0.00002965796,0.0004718698,0.00004574266,0.0001216526,0.00005366933,0.001128485,0.0008410752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003604835,"about_ca_system_score_gemma":0.0003316409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001908769,"about_ca_topic_score_gemma":0.0001403741,"domain_scores_codex":[0.9977321,0.000523723,0.0004406715,0.0005202272,0.0002835336,0.0004997264],"domain_scores_gemma":[0.9983423,0.0004345714,0.0001964466,0.0004882762,0.0001836931,0.000354704],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005324456,0.0001350598,0.002120906,0.0001097336,0.000005749849,0.000001275329,0.0003418468,4.585183e-7,0.2813703,0.006061526,0.02629438,0.6835056],"study_design_scores_gemma":[0.001139595,0.00010472,0.1584416,0.00009472298,0.00005954403,0.000010608,0.0004424118,0.006883885,0.004472049,0.001452972,0.8265923,0.0003055048],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.3997934,0.000144531,0.179424,0.4042889,0.0006512203,0.005487556,0.0001821674,0.001216501,0.008811672],"genre_scores_gemma":[0.8990504,0.00003215502,0.09548146,0.002941901,0.0003269514,0.001252836,0.0001310617,0.0000379446,0.0007453592],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.800298,"threshold_uncertainty_score":0.9999369,"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."}}