{"id":"W747590341","doi":"10.1016/j.neures.2015.06.007","title":"Sequential hypothesis testing for automatic detection of task-related changes in cerebral perfusion in a brain–computer interface","year":2015,"lang":"en","type":"article","venue":"Neuroscience Research","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Holland Bloorview Kids Rehabilitation Hospital; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Interface (matter); Task (project management); Computer science; Brain–computer interface; Perfusion; Cerebral perfusion pressure; Neuroscience; Artificial intelligence; Medicine; Psychology; Cardiology; Operating system; Electroencephalography; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.002866333,0.0001658765,0.0002553213,0.001029434,0.0001461074,0.0001516811,0.0008036915,0.00009931344,0.000004921792],"category_scores_gemma":[0.009490254,0.0001488227,0.00004310685,0.002547574,0.0004517045,0.0003706098,0.0004584114,0.0004833493,0.00001030416],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001731594,"about_ca_system_score_gemma":0.0001875979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002142232,"about_ca_topic_score_gemma":0.0002581674,"domain_scores_codex":[0.9962764,0.0008363318,0.0004249045,0.0008033038,0.0008792712,0.0007797905],"domain_scores_gemma":[0.9965693,0.002706484,0.0001200368,0.0002935519,0.0001639385,0.0001466382],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004013129,0.0001269666,0.0008350195,0.00005026816,2.503382e-7,0.0000153875,0.001257381,0.001144253,0.9488565,0.00001827724,0.00005647349,0.04759905],"study_design_scores_gemma":[0.0005542185,0.001031292,0.003302169,0.0001364336,7.31781e-7,0.0000343096,0.0000922149,0.4447685,0.5494053,0.0004964189,0.00007408008,0.0001042153],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961137,0.00001266817,0.001311911,0.001118839,0.0005020183,0.0007447323,0.000006099712,0.00006926269,0.0001207743],"genre_scores_gemma":[0.9985976,0.000002587817,0.0009836918,0.0001611155,0.00005594896,0.00005911085,1.573834e-7,0.00002115597,0.0001185895],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4436243,"threshold_uncertainty_score":0.9988532,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2210182043326967,"score_gpt":0.3889008200917866,"score_spread":0.1678826157590899,"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."}}