{"id":"W2122003336","doi":"10.1109/tnsre.2006.875585","title":"BCI meeting 2005-workshop on clinical issues and applications","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":154,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Institute of Biomedical Imaging and Bioengineering","keywords":"Brain–computer interface; Government (linguistics); Computer science; Interface (matter); State (computer science); Engineering ethics; Human–computer interaction; Psychology; Engineering; Electroencephalography; Neuroscience","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002267212,0.0001541635,0.0001832561,0.000132146,0.0001873194,0.0001048839,0.00006876972,0.00008147035,0.000002658652],"category_scores_gemma":[0.00003355374,0.0001336458,0.00006410759,0.0001411907,0.00008030182,0.0001481628,0.000001581934,0.0002192226,0.000006420792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002131028,"about_ca_system_score_gemma":0.000004489054,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005473677,"about_ca_topic_score_gemma":0.000008705796,"domain_scores_codex":[0.998788,0.00009171615,0.0003910581,0.0003933925,0.0001510287,0.0001848199],"domain_scores_gemma":[0.9980534,0.001634482,0.00005861184,0.0001547962,0.00002252431,0.00007619786],"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":[0.00002949248,0.0001892627,0.0001403366,0.0002136147,0.00001117277,0.00000242424,0.0002275009,0.9448923,0.0394497,0.00202654,0.0003428643,0.01247478],"study_design_scores_gemma":[0.001430206,0.001071608,0.004654536,0.000839059,0.00005208799,0.00009679361,0.0005291751,0.9274181,0.02017805,0.0001535314,0.04263609,0.0009407267],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.843833,0.000351743,0.1519945,0.001274963,0.001219723,0.0007482058,0.0000222933,0.00032594,0.0002296349],"genre_scores_gemma":[0.9986601,0.00006989609,0.0004509746,0.00005039137,0.0002108268,0.0001015229,5.373756e-7,0.00001870345,0.0004370682],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1548271,"threshold_uncertainty_score":0.5449916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02061236689409951,"score_gpt":0.2901964517987628,"score_spread":0.2695840849046633,"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."}}