{"id":"W2147612083","doi":"10.1109/emb.2007.910270","title":"A General-Purpose MR-Compatible Robotic System","year":2008,"lang":"en","type":"article","venue":"IEEE Engineering in Medicine and Biology Magazine","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"National Cancer Institute; National Heart, Lung, and Blood Institute; National Institutes of Health; National and Kapodistrian University of Athens","keywords":"Modalities; Computer science; Interface (matter); Rapid prototyping; Medical robotics; General purpose; Control system; Manipulator (device); Systems engineering; Medical physics; Robot; Artificial intelligence; Engineering; Medicine; Operating system; Mechanical engineering; Computer architecture","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":[0.0004217846,0.0005986388,0.0005203407,0.0005442693,0.0004023233,0.0006102697,0.0009222931,0.0007841207,0.004879743],"category_scores_gemma":[0.00047721,0.0002977324,0.0002706213,0.0003279568,0.0002983817,0.0005846416,0.0006589429,0.0005517128,0.003624345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002116102,"about_ca_system_score_gemma":0.0007544398,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006712062,"about_ca_topic_score_gemma":0.0008264966,"domain_scores_codex":[0.9995868,0.00005216799,0.00002674148,0.00009735682,0.0002136333,0.00002338715],"domain_scores_gemma":[0.9997872,0.00002436445,0.00002818474,0.00003194585,0.00009302762,0.00003537662],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004012159,0.0001732702,0.001302677,0.001275386,0.00004592071,0.001848219,0.0001978025,0.003450497,0.4693235,0.008508752,0.02237705,0.4910958],"study_design_scores_gemma":[0.0001493408,0.003300389,0.006959116,0.0003188266,0.0001925674,0.01721387,0.0001075836,0.02903814,0.2258223,0.002307958,0.7143047,0.0002852383],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05004572,0.006378045,0.8686799,0.000838042,0.0008026878,0.001456127,0.0005718918,0.01470533,0.05652216],"genre_scores_gemma":[0.2493701,0.00480656,0.6716056,0.001329108,0.0003751651,0.001010668,0.0008800377,0.0003682812,0.07025456],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004879743,"threshold_uncertainty_score":0.01632434,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04491845710119464,"score_gpt":0.3109723575293146,"score_spread":0.26605390042812,"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."}}