{"id":"W2157260479","doi":"10.1109/iembs.2005.1615647","title":"Real-time Magnetic Resonance Gradient-based Propulsion of a Wireless Microdevice Using Pre-Acquired Roadmap and Dedicated Software Architecture","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Propulsion; Imaging phantom; Computer science; Scanner; Software; Wireless; Computation; Latency (audio); Real-time computing; Aerospace engineering; Physics; Engineering; Artificial intelligence; Telecommunications; Optics","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":[0.0003752482,0.000494324,0.0003078971,0.0002913259,0.0001418373,0.0005003132,0.0007803106,0.0003216429,0.001574956],"category_scores_gemma":[0.00116565,0.0001950762,0.0001373291,0.0001242241,0.0002644957,0.0004735585,0.0003546124,0.0002971494,0.0004285923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001752412,"about_ca_system_score_gemma":0.0003523983,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002888927,"about_ca_topic_score_gemma":0.0004540784,"domain_scores_codex":[0.9998552,0.00002503595,0.000009561938,0.00003180457,0.00006503624,0.00001333375],"domain_scores_gemma":[0.9995599,0.0002027885,0.00004617457,0.00006091858,0.0001063938,0.00002370362],"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":[0.0006057393,0.00008121438,0.001717848,0.00025426,0.00005266567,0.0003926713,0.0003334804,0.01957753,0.4782159,0.003842229,0.001724232,0.4932022],"study_design_scores_gemma":[0.0001490132,0.0008818363,0.003539086,0.00005558201,0.00009742144,0.001900399,0.00007941569,0.4017171,0.5707272,0.002036256,0.01871188,0.0001048737],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03532855,0.00007666734,0.9596937,0.00005523347,0.00003306468,0.00005557788,0.000023226,0.003850503,0.0008834495],"genre_scores_gemma":[0.495093,0.0001457729,0.5010637,0.00006309788,0.00002679766,0.0001633133,0.00009836552,0.0003849679,0.002961067],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001574956,"threshold_uncertainty_score":0.005268753,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01049076151266992,"score_gpt":0.2785874336811072,"score_spread":0.2680966721684372,"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."}}