{"id":"W1914838583","doi":"10.1002/rcs.1692","title":"Toward teleoperated needle steering under continuous MRI guidance for prostate percutaneous interventions","year":2015,"lang":"en","type":"article","venue":"International Journal of Medical Robotics and Computer Assisted Surgery","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Cancer Care Ontario","keywords":"Bevel; Teleoperation; Computer science; Haptic technology; Simulation; Robot; Scanner; Imaging phantom; Biomedical engineering; Medicine; Artificial intelligence; Engineering; Radiology; Mechanical engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003104669,0.000416396,0.0002309713,0.0001586633,0.0001439178,0.0003628593,0.0006535423,0.0004584682,0.001785291],"category_scores_gemma":[0.0005346674,0.0002278562,0.0002337254,0.00009561101,0.0003215248,0.0004160029,0.0004660559,0.0002497642,0.0005332339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001121411,"about_ca_system_score_gemma":0.0003906586,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003206738,"about_ca_topic_score_gemma":0.0004571573,"domain_scores_codex":[0.9997326,0.00005560974,0.00001344412,0.00005857115,0.0001125852,0.00002714911],"domain_scores_gemma":[0.9997029,0.00005733029,0.0000666328,0.000047306,0.00008377431,0.00004207234],"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":[0.0004094963,0.0001543577,0.001740614,0.0001985253,0.00002777165,0.000326203,0.00023094,0.007195657,0.8792973,0.000872036,0.0006290208,0.108918],"study_design_scores_gemma":[0.0002031797,0.002990771,0.01281109,0.00006519033,0.0001225902,0.003616277,0.0001485471,0.2755491,0.6797264,0.001738401,0.0228529,0.0001756376],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.188491,0.0003803975,0.8062019,0.0002081179,0.0000685211,0.0001762849,0.00005037932,0.001745268,0.002678277],"genre_scores_gemma":[0.7163704,0.0002377582,0.279765,0.0001627812,0.0000423846,0.0001422744,0.00007622552,0.00008985348,0.003113349],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001785291,"threshold_uncertainty_score":0.005972326,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05452660880697585,"score_gpt":0.2946928194210719,"score_spread":0.240166210614096,"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."}}