{"id":"W1562432672","doi":"10.3389/fnsys.2015.00072","title":"Future think: cautiously optimistic about brain augmentation using tissue engineering and machine interface","year":2015,"lang":"en","type":"article","venue":"Frontiers in Systems Neuroscience","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"International Collaboration On Repair Discoveries; University of Victoria","funders":"","keywords":"Brain–computer interface; Interface (matter); Computer science; Volume (thermodynamics); Brain size; Neuroscience; Artificial intelligence; Psychology; Medicine; Operating system; Magnetic resonance imaging; Physics; Radiology","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":[0.0004901738,0.0002527551,0.0002911759,0.0002693475,0.0001363265,0.0003680379,0.0004996449,0.00008092888,9.503e-7],"category_scores_gemma":[0.0004700387,0.0002369315,0.00002261234,0.0005708704,0.0001720904,0.0006019204,0.000170581,0.0002719663,0.00000275699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001642817,"about_ca_system_score_gemma":0.00006217697,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001060031,"about_ca_topic_score_gemma":0.000003992767,"domain_scores_codex":[0.9978047,0.0002074536,0.0003811001,0.000732391,0.0004401874,0.0004341489],"domain_scores_gemma":[0.9992457,0.00008681801,0.0001500783,0.0002759837,0.00003242131,0.0002089793],"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":[0.00005365409,0.00006729985,0.00225129,0.000178292,0.000002654463,0.0001830861,0.005611086,0.4247793,0.5591533,0.0004716087,0.005357568,0.001890864],"study_design_scores_gemma":[0.0005152638,0.0001411664,0.0003630839,0.0001472091,0.000005160226,0.0003546053,0.0006120543,0.9610276,0.02964317,0.00002737417,0.006862076,0.0003012938],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6604642,0.00217828,0.3220066,0.0004191131,0.01404032,0.0005652821,0.00002518075,0.0001754389,0.0001255675],"genre_scores_gemma":[0.9950171,0.00002718933,0.003922321,0.0003420915,0.0001738329,0.00001039447,8.234343e-7,0.00002645685,0.0004798368],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5362482,"threshold_uncertainty_score":0.9661785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03221872486590428,"score_gpt":0.2779203034571744,"score_spread":0.2457015785912702,"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."}}