{"id":"W2080848961","doi":"10.1118/1.2241498","title":"TU‐C‐330A‐05: Optimization of Outer Volume Suppression for Improved Prostate MR Spectroscopic Imaging","year":2006,"lang":"en","type":"article","venue":"Medical Physics","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; National Research Council Institute for Biodiagnostics; University of Manitoba; CancerCare Manitoba","funders":"","keywords":"Voxel; Prostate; SIGNAL (programming language); Imaging phantom; Contamination; Nuclear magnetic resonance; Materials science; Spectral line; Nuclear medicine; Physics; Medicine; Computer science; Radiology; Biology; Internal medicine","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":[0.0002396606,0.0004335174,0.0002830059,0.0002189415,0.0001431508,0.0003641946,0.0004451633,0.0003594352,0.001572093],"category_scores_gemma":[0.0004637084,0.0001730851,0.0002311002,0.0002718753,0.0001682823,0.0001800914,0.0002755648,0.0002347268,0.0003376421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000310334,"about_ca_system_score_gemma":0.0005940837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002090039,"about_ca_topic_score_gemma":0.002585397,"domain_scores_codex":[0.9998982,0.00001674112,0.000004253363,0.00002213724,0.00003599138,0.0000226096],"domain_scores_gemma":[0.9998432,0.0000311874,0.00004161476,0.00001547984,0.00004486007,0.00002364963],"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":[0.0006178422,0.0002867947,0.001369438,0.0002259246,0.00006331044,0.0001159694,0.00006280038,0.06895041,0.8760737,0.0007282162,0.001072187,0.05043345],"study_design_scores_gemma":[0.0001128125,0.001346863,0.004952616,0.00001434867,0.00008945426,0.0003304429,0.00003568446,0.3821561,0.6025595,0.0002223839,0.008126903,0.00005280062],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7894388,0.0007535632,0.2005864,0.000129397,0.000055022,0.0001173585,0.00022236,0.002199801,0.006497227],"genre_scores_gemma":[0.8867456,0.0001565119,0.1108855,0.00008078429,0.00001003389,0.00006813972,0.0002479035,0.0003110422,0.001494459],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002090039,"threshold_uncertainty_score":0.005259216,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007209330969766842,"score_gpt":0.295067660823261,"score_spread":0.2878583298534941,"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."}}