{"id":"W1982333157","doi":"10.1109/tbme.2012.2192118","title":"Biopsy Needle Artifact Localization in MRI-Guided Robotic Transrectal Prostate Intervention","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Engineering","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"National Institute of Biomedical Imaging and Bioengineering","keywords":"Artifact (error); Scanner; Magnetic resonance imaging; Prostate; Medicine; Radiology; Interventional magnetic resonance imaging; Biomedical engineering; Nuclear medicine; Computer science; Computer vision; Artificial intelligence; Cancer","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":[0.001266709,0.0002769066,0.0002783142,0.0008020619,0.000152081,0.0004175941,0.000405724,0.0005175514,0.0003183763],"category_scores_gemma":[0.008058724,0.0002783017,0.0001960267,0.0005162742,0.0004567156,0.0004508456,0.0003659863,0.0002200452,0.0001447726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002806206,"about_ca_system_score_gemma":0.0002553412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009738189,"about_ca_topic_score_gemma":0.001752232,"domain_scores_codex":[0.9987397,0.0005488276,0.00008566126,0.0001056261,0.0004851444,0.00003513677],"domain_scores_gemma":[0.9973254,0.001373183,0.0006952463,0.0001663868,0.0003648607,0.00007482433],"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":[0.003291133,0.0001448375,0.05109531,0.001055313,0.0001642808,0.004596894,0.0008812234,0.01833034,0.5697733,0.000666573,0.0003486827,0.3496521],"study_design_scores_gemma":[0.0001060854,0.003737348,0.2776706,0.0001391824,0.0005569319,0.04426242,0.0005100913,0.1167972,0.5501878,0.001299819,0.004492013,0.0002406763],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8120371,0.010031,0.1760482,0.0001333069,0.00005276703,0.00007386259,0.00004820455,0.0004419495,0.001133697],"genre_scores_gemma":[0.9631609,0.0009633919,0.0352957,0.00006200429,0.00003092441,0.00001316067,0.00004284725,0.00005917788,0.0003718323],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001266709,"threshold_uncertainty_score":0.006699026,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01145028397917253,"score_gpt":0.2306035195500023,"score_spread":0.2191532355708298,"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."}}