{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005497068,0.0002533614,0.00024738,0.001219174,0.0001143168,0.0002924898,0.0001871436,0.0002847008,0.0008279892],"category_scores_gemma":[0.002286375,0.00008727699,0.0002108825,0.0005144827,0.0001878395,0.0003511332,0.0001469913,0.0002822267,0.00025686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001552729,"about_ca_system_score_gemma":0.000138789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007186863,"about_ca_topic_score_gemma":0.0007286762,"domain_scores_codex":[0.9997948,0.0000473881,0.00001271478,0.00003262193,0.00009438119,0.00001812283],"domain_scores_gemma":[0.9993173,0.0004041127,0.00009764118,0.00005682101,0.00009855613,0.00002558497],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006532518,0.0002200676,0.02277835,0.0003024238,0.0001077211,0.0002958424,0.0001823694,0.02139445,0.2782448,0.002305742,0.001561451,0.6719536],"study_design_scores_gemma":[0.00003964447,0.0004222787,0.1380093,0.00006600291,0.0001473589,0.001768555,0.0001299145,0.7304862,0.1201679,0.003180125,0.005506636,0.00007609019],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6063168,0.002437034,0.3856237,0.0003090486,0.0001220398,0.00006155735,0.0004152822,0.001049211,0.003665366],"genre_scores_gemma":[0.8992366,0.000584637,0.0992131,0.00003223025,0.00005931603,0.00002668206,0.0002018352,0.00002741941,0.0006182136],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001219174,"threshold_uncertainty_score":0.002907157,"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."}}