{"id":"W3089663612","doi":"10.1016/j.brs.2020.09.012","title":"MEP-ART: A system for real-time feedback and analysis of transcranial magnetic stimulation motor evoked potentials","year":2020,"lang":"en","type":"letter","venue":"Brain stimulation","topic":"Transcranial Magnetic Stimulation Studies","field":"Neuroscience","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. Department of Veterans Affairs; U.S. Department of Defense","keywords":"Transcranial magnetic stimulation; Electromyography; Neuroscience; Physical medicine and rehabilitation; Psychology; Stimulation; Motor cortex; Functional electrical stimulation; Primary motor cortex; Scopus; Medicine; Chemistry; MEDLINE","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003289234,0.0007166808,0.001743061,0.001060208,0.0003079267,0.000142719,0.0003419877,0.0006655043,0.000285147],"category_scores_gemma":[0.0009971604,0.0007584398,0.0006932552,0.001636743,0.0002787992,0.0002399979,0.00005522985,0.0003907759,0.00005702029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001178548,"about_ca_system_score_gemma":0.00008018517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005565281,"about_ca_topic_score_gemma":0.000005668497,"domain_scores_codex":[0.9947602,0.0005997672,0.001551037,0.001425259,0.001119373,0.0005443682],"domain_scores_gemma":[0.9936066,0.004572887,0.0008080428,0.0005403542,0.0003398858,0.0001322757],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00209084,0.0001128794,0.0002789922,0.002251175,0.0008178147,0.00006384947,0.001317955,0.04513048,0.8749727,0.0002669025,0.06973168,0.002964737],"study_design_scores_gemma":[0.007452657,0.001504548,0.04758538,0.0002672283,0.009741853,0.000009328334,0.00002948676,0.9158922,0.0008808895,0.0004752127,0.01487594,0.001285261],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2131541,0.0007398279,0.2336891,0.4949605,0.003040786,0.02939619,0.01754666,0.003023132,0.004449782],"genre_scores_gemma":[0.9607071,0.00004320578,0.003853926,0.02914727,0.001488709,0.0002892511,0.001649539,0.0002330727,0.002587917],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8740918,"threshold_uncertainty_score":0.9994867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0293624489969726,"score_gpt":0.26685843715237,"score_spread":0.2374959881553974,"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."}}