{"id":"W2128935799","doi":"10.1109/ner.2011.5910527","title":"Quantitative modeling of electric field in deep brain stimulation: Study of medium brain tissue and stimulation pulse parameters","year":2011,"lang":"en","type":"article","venue":"","topic":"Neurological disorders and treatments","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Deep brain stimulation; Finite-difference time-domain method; Brain tissue; Electromagnetic field; Stimulation; White matter; Biomedical engineering; Electric field; Electrode; Computer science; Materials science; Neuroscience; Physics; Engineering; Medicine; Optics","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":[0.0002778505,0.0003612701,0.0002547585,0.0002019926,0.0001015953,0.0004084364,0.0004388765,0.0005499402,0.0007592497],"category_scores_gemma":[0.001104535,0.0001806822,0.0002557793,0.0001914808,0.0003471454,0.0006599184,0.0001964194,0.0003238879,0.0002020818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004360263,"about_ca_system_score_gemma":0.0003315172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007449669,"about_ca_topic_score_gemma":0.0005251116,"domain_scores_codex":[0.9998927,0.00002635913,0.000004952856,0.00001516096,0.00005217395,0.000008520681],"domain_scores_gemma":[0.9995881,0.0003002763,0.00003502147,0.00002510045,0.00004214267,0.000009392887],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006008213,0.00003121045,0.000661103,0.0001054372,0.00001187108,0.0001320934,0.00008995464,0.8551342,0.117046,0.00847012,0.00019223,0.01806574],"study_design_scores_gemma":[0.000006060092,0.00004203775,0.000299119,0.000007252787,0.000005151435,0.0001360974,0.0000141626,0.9810043,0.01548712,0.00198638,0.001003896,0.000008450653],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06237636,0.0003692239,0.9333538,0.0001257434,0.00002225009,0.00003803771,0.0000593964,0.0001958517,0.003459299],"genre_scores_gemma":[0.8909056,0.0007521493,0.1034433,0.00006424691,0.00001803707,0.00008836368,0.00009321501,0.00008759981,0.004547467],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0007592497,"threshold_uncertainty_score":0.003163576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07153677046127747,"score_gpt":0.3431994164078409,"score_spread":0.2716626459465634,"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."}}