{"id":"W1985268169","doi":"10.1109/ner.2011.5910635","title":"Electromagnetic modeling and design optimization of intra-cortical micro-electrodes","year":2011,"lang":"en","type":"article","venue":"","topic":"Neuroscience and Neural Engineering","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Finite-difference time-domain method; Electrode; Electromagnetic field; Materials science; Computer science; Electric field; Finite element method; Biocompatibility; Biomedical engineering; Electronic engineering; Engineering; Optics; Physics","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":[0.0002183509,0.0004341127,0.0003318723,0.0001679812,0.0001310307,0.0005107828,0.0005144044,0.00070541,0.001023958],"category_scores_gemma":[0.0006374196,0.0002920913,0.0003593079,0.0001768945,0.0002625896,0.0004391517,0.0002280294,0.0002296177,0.0003664225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003749386,"about_ca_system_score_gemma":0.0004161246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006097055,"about_ca_topic_score_gemma":0.0007994251,"domain_scores_codex":[0.9998754,0.00003141833,0.000005420363,0.00002016319,0.00005645574,0.00001117404],"domain_scores_gemma":[0.9998498,0.00007428764,0.00002117452,0.00001706311,0.00003138941,0.0000062144],"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":[0.00004660792,0.00002229803,0.0003129536,0.00009625258,0.00001644964,0.0001187404,0.00003761144,0.9443855,0.03919455,0.002062278,0.0002076904,0.01349913],"study_design_scores_gemma":[0.000009065438,0.00005325976,0.0002317845,0.000006631,0.000009934204,0.00007900997,0.00001404133,0.9879848,0.009315015,0.0009158324,0.001375371,0.000005217245],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09628873,0.0008137769,0.8905631,0.0003253225,0.00004831297,0.00007040661,0.0000861548,0.0003702164,0.01143394],"genre_scores_gemma":[0.8693653,0.000898027,0.1217933,0.00006505409,0.00001918994,0.0001686422,0.0000710071,0.0000853926,0.007534179],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001023958,"threshold_uncertainty_score":0.003425419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05434312877305794,"score_gpt":0.2319058449855886,"score_spread":0.1775627162125307,"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."}}