{"id":"W2122393462","doi":"10.1109/iembs.2007.4352545","title":"Discrete Fourier Analysis of Ultrasound RF Time Series for Detection of Prostate Cancer","year":2007,"lang":"en","type":"article","venue":"Conference proceedings","topic":"Spectroscopy Techniques in Biomedical and Chemical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Ultrasound; Prostate cancer; Artificial intelligence; Fourier analysis; Radio frequency; Feature (linguistics); Sensitivity (control systems); Pattern recognition (psychology); Fractal dimension; Series (stratigraphy); Data set; Fourier transform; Computer science; Prostate; Fractal; Cancer; Medicine; Mathematics; Radiology; Biology; Internal medicine; Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002907865,0.00009122846,0.0001914308,0.00009332229,0.00002928511,0.00001076919,0.0001631033,0.0001293145,0.00005772171],"category_scores_gemma":[0.0002827923,0.00007620872,0.0001046524,0.0003420921,0.0002813796,0.000006652148,0.00005399296,0.00006235042,2.514739e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000150295,"about_ca_system_score_gemma":0.00004605093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001942658,"about_ca_topic_score_gemma":0.000007648306,"domain_scores_codex":[0.9991597,0.000001995651,0.0002242797,0.0002207526,0.0001775875,0.0002157183],"domain_scores_gemma":[0.9992283,0.00002128066,0.0001189386,0.00008454573,0.0004771862,0.00006976593],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003482117,0.00002105012,0.005212147,0.00007448633,0.0001754251,5.761921e-8,0.00007764907,9.854232e-8,0.9903252,0.0001491379,0.0002047414,0.003411853],"study_design_scores_gemma":[0.0001266003,0.0003145496,0.001746243,0.00002101932,0.0001155622,9.230299e-7,0.00007974987,0.0001013791,0.9928368,0.0006135291,0.003955491,0.00008813166],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9829868,0.0001130133,0.01546673,0.00007195997,0.00001715,0.0002149845,0.00006351098,0.00001185167,0.001053982],"genre_scores_gemma":[0.9964563,0.0002188699,0.001993615,0.00001768018,0.00004719922,0.00005596153,0.00004311626,0.000008519492,0.001158762],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01347311,"threshold_uncertainty_score":0.3107702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01004796374185118,"score_gpt":0.3195294909378978,"score_spread":0.3094815271960466,"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."}}