{"id":"W2188705042","doi":"10.1109/tro.2015.2489518","title":"Dipole Field Navigation: Theory and Proof of Concept","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Robotics","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies; Canada Foundation for Innovation","keywords":"Microscale chemistry; Magnetic field; Scanner; Dipole; Computer science; Field (mathematics); Magnetic dipole; Field strength; Physics; Artificial intelligence; Mathematics","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":[0.0006269977,0.0005769177,0.0005173028,0.0004736269,0.0004055885,0.001040094,0.001033397,0.001574479,0.006597503],"category_scores_gemma":[0.0006710018,0.0005239455,0.0004602625,0.0003738302,0.000963805,0.0009423097,0.0008085115,0.0009693386,0.001630799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005684483,"about_ca_system_score_gemma":0.000705423,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006147138,"about_ca_topic_score_gemma":0.000477603,"domain_scores_codex":[0.9997516,0.00004269476,0.00000941728,0.00003388703,0.0001460177,0.0000163304],"domain_scores_gemma":[0.9997777,0.000108771,0.00002529293,0.00001827483,0.0000555814,0.00001444705],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001337821,0.0001578373,0.000561189,0.001934334,0.00005696541,0.0006831366,0.0004607983,0.09827659,0.1000978,0.6313657,0.01586197,0.1504099],"study_design_scores_gemma":[0.0001874526,0.0008371844,0.0004869256,0.0003643011,0.00004081152,0.001673203,0.0001930347,0.7148834,0.04493693,0.1047331,0.13149,0.000173721],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001366147,0.001055473,0.9820114,0.0006098458,0.0002334993,0.0001186998,0.0000581484,0.0002589736,0.01428775],"genre_scores_gemma":[0.165214,0.00413953,0.8129695,0.0006593476,0.0002867397,0.001032563,0.0001653007,0.0001213494,0.01541153],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006597503,"threshold_uncertainty_score":0.02207083,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03013697583948406,"score_gpt":0.3201746393050995,"score_spread":0.2900376634656154,"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."}}