{"id":"W2804432531","doi":"10.3389/fncom.2018.00040","title":"Modeling Current Sources for Neural Stimulation in COMSOL","year":2018,"lang":"en","type":"article","venue":"Frontiers in Computational Neuroscience","topic":"Neuroscience and Neural Engineering","field":"Neuroscience","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; Duke University","keywords":"Multiphysics; Electrode; Computer science; Substrate (aquarium); Materials science; Current source; Current (fluid); Finite element method; Electrode array; Silicone; Biomedical engineering; Electronic engineering; Optoelectronics; Biological system; Electrical engineering; Chemistry; Physics; Engineering; Composite material","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006026521,0.001005845,0.0005864995,0.000788427,0.0005240696,0.001351697,0.001844161,0.002007161,0.02221682],"category_scores_gemma":[0.001951743,0.0006446897,0.001357525,0.0006010308,0.0005533625,0.001040367,0.001193488,0.001297218,0.005237778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000812794,"about_ca_system_score_gemma":0.001476721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002493438,"about_ca_topic_score_gemma":0.003519767,"domain_scores_codex":[0.9995198,0.00007667721,0.00002590973,0.00003957739,0.0003061912,0.0000319054],"domain_scores_gemma":[0.9989604,0.0004923945,0.0001038038,0.0001016753,0.0003042201,0.00003749203],"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":[0.00004042341,0.00004466635,0.0006167382,0.0006634163,0.00006888507,0.0001734949,0.0002257369,0.9025005,0.01023715,0.03006039,0.01086542,0.04450311],"study_design_scores_gemma":[0.00002710185,0.00002368676,0.00008810525,0.00009302557,0.00001500452,0.0001174576,0.00003689174,0.9456734,0.004006421,0.009386085,0.04051169,0.00002113209],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004527427,0.0005036848,0.9682887,0.0006093431,0.0001690209,0.000167348,0.0006778913,0.003358356,0.02169827],"genre_scores_gemma":[0.2032202,0.002224298,0.7439537,0.0007952573,0.0001705153,0.00233753,0.002237668,0.002688749,0.04237206],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02221682,"threshold_uncertainty_score":0.0743227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06464651854647363,"score_gpt":0.3203746748439333,"score_spread":0.2557281562974597,"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."}}