{"id":"W2743793037","doi":"10.1162/neco_a_01001","title":"Toward an Open-Ended BCI: A User-Centered Coadaptive Design","year":2017,"lang":"en","type":"article","venue":"Neural Computation","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Brain–computer interface; Computer science; Brain activity and meditation; Human–computer interaction; Neurophysiology; Neurofeedback; Modality (human–computer interaction); Electroencephalography; Psychology; Machine learning; 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":[0.001142555,0.00074957,0.0003703702,0.0004271407,0.0003423379,0.001179491,0.001452356,0.001042861,0.003038508],"category_scores_gemma":[0.003398397,0.0002972559,0.0003307434,0.000225663,0.0009579596,0.001150258,0.001210375,0.001135711,0.001247417],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003009634,"about_ca_system_score_gemma":0.0003283989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003653592,"about_ca_topic_score_gemma":0.0005772427,"domain_scores_codex":[0.9985783,0.0004876854,0.0000933346,0.000316208,0.000456234,0.00006820877],"domain_scores_gemma":[0.9986795,0.0003533038,0.00009689986,0.0001677441,0.0005509703,0.0001515929],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007354057,0.0008508731,0.002436582,0.0008269178,0.0001406466,0.0004900302,0.002324329,0.01123921,0.4667633,0.01882216,0.003433329,0.4919372],"study_design_scores_gemma":[0.0006862557,0.01081836,0.02602172,0.0006233564,0.0004892594,0.006124276,0.001368854,0.3836502,0.3955368,0.05347384,0.1207872,0.0004201487],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04110742,0.0002748589,0.9523416,0.0003933554,0.00008439965,0.0004725268,0.00003539955,0.0006478849,0.004642596],"genre_scores_gemma":[0.2837212,0.0003787203,0.7067231,0.0006603771,0.00006334323,0.0009154916,0.0001246273,0.0001787623,0.007234393],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003038508,"threshold_uncertainty_score":0.0101648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2403202271892095,"score_gpt":0.3714613901553717,"score_spread":0.1311411629661622,"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."}}