{"id":"W2914212446","doi":"10.3389/fnhum.2019.00024","title":"Evaluating If Children Can Use Simple Brain Computer Interfaces","year":2019,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hotchkiss Brain Institute; Alberta Children's Hospital; University of Calgary","funders":"Heart and Stroke Foundation of Canada","keywords":"Brain–computer interface; Electroencephalography; Motor imagery; Task (project management); Set (abstract data type); Sensorimotor rhythm; Computer science; Cognition; Population; Physical medicine and rehabilitation; Audiology; Psychology; Medicine; Neuroscience","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001475649,0.0005734721,0.0002646117,0.0004721833,0.0001516438,0.0006803008,0.0003455321,0.0004667896,0.003851318],"category_scores_gemma":[0.007841868,0.0001499064,0.0004766965,0.0002111363,0.0003105909,0.0008418743,0.0004079886,0.0003875075,0.0009711893],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002071336,"about_ca_system_score_gemma":0.000300655,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001197134,"about_ca_topic_score_gemma":0.002030751,"domain_scores_codex":[0.9993935,0.0001121308,0.0001051837,0.0001181111,0.0001639085,0.0001071734],"domain_scores_gemma":[0.9954662,0.001719478,0.001325629,0.0002077943,0.0008620683,0.0004188012],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007785887,0.0007535398,0.9462454,0.0003632688,0.00009976124,0.0001874509,0.001211862,0.0003952224,0.003959316,0.0001013648,0.0005568638,0.04534741],"study_design_scores_gemma":[0.00004466706,0.004217483,0.988184,0.00009572272,0.0001237275,0.0006278604,0.0008088047,0.000675067,0.003319225,0.0001412978,0.00174198,0.00002007196],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979852,0.000114267,0.0003553181,0.00002045305,0.00000393588,0.00008584287,0.0002759454,0.00001777902,0.001141214],"genre_scores_gemma":[0.9959354,0.0003073791,0.002344852,0.00002857078,0.000005719565,0.0001756491,0.000589664,0.000007146587,0.0006056432],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003851318,"threshold_uncertainty_score":0.01288396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05213901387928774,"score_gpt":0.322835521763329,"score_spread":0.2706965078840413,"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."}}