{"id":"W2011111213","doi":"10.1186/1743-0003-6-39","title":"Single-trial classification of NIRS signals during emotional induction tasks: towards a corporeal machine interface","year":2009,"lang":"en","type":"article","venue":"Journal of NeuroEngineering and Rehabilitation","topic":"Optical Imaging and Spectroscopy Techniques","field":"Medicine","cited_by":145,"is_retracted":false,"has_abstract":true,"ca_institutions":"Holland Bloorview Kids Rehabilitation Hospital; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Children's Hospital Foundation","keywords":"Linear discriminant analysis; Support vector machine; Artificial intelligence; Brain–computer interface; Stimulus (psychology); Pattern recognition (psychology); Classifier (UML); Feature selection; Computer science; Speech recognition; Electroencephalography; Psychology; Cognitive psychology; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002311149,0.00009867967,0.0002532562,0.0002821621,0.00002637215,0.00001572064,0.00003566822,0.00004918662,0.000003747325],"category_scores_gemma":[0.0005148607,0.00008148972,0.00009524768,0.000148183,0.00005619238,0.0001681655,0.000006114597,0.0002552413,1.61765e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007126277,"about_ca_system_score_gemma":0.00002936818,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002271018,"about_ca_topic_score_gemma":7.693044e-8,"domain_scores_codex":[0.9990078,0.00003752573,0.0005022915,0.0001102898,0.0002455738,0.00009650774],"domain_scores_gemma":[0.999291,0.00008484195,0.0002391568,0.00008610052,0.0002188476,0.00008003251],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.003269609,0.0003378786,0.0005846355,0.0001324043,0.00002061935,0.00000619516,0.0002202433,0.0005099426,0.9885871,0.0001649412,0.00005621007,0.006110238],"study_design_scores_gemma":[0.01466649,0.02816728,0.8113353,0.001445826,0.0002173094,0.001052788,0.0002226482,0.01704579,0.1236304,0.001801023,0.0001513966,0.0002636646],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9870884,0.00009963683,0.009033928,0.003302816,0.0001804317,0.0001632835,0.000001742089,0.00003979804,0.00008995217],"genre_scores_gemma":[0.9858553,0.00004602558,0.01389265,0.0000149839,0.0001590425,0.000001267781,0.000002207109,0.000009483118,0.00001902591],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8649567,"threshold_uncertainty_score":0.3323054,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01597206873956293,"score_gpt":0.2939885926264639,"score_spread":0.278016523886901,"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."}}