{"id":"W2559696084","doi":"10.1371/journal.pcbi.1004914","title":"Detecting Mild Traumatic Brain Injury Using Resting State Magnetoencephalographic Connectivity","year":2016,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Armed Forces; Sunnybrook Hospital; SickKids Foundation; University of Toronto; Hospital for Sick Children; Simon Fraser University","funders":"","keywords":"Magnetoencephalography; Resting state fMRI; Traumatic brain injury; Functional connectivity; Neuroimaging; Neuroscience; Brain mapping; Poison control; Medicine; Electroencephalography; Psychology; Psychiatry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000328433,0.00031586,0.0002101945,0.0009921059,0.0001435262,0.0004156439,0.0001919356,0.0003192757,0.0006943372],"category_scores_gemma":[0.00238925,0.0001052739,0.000173894,0.0004347252,0.0002353262,0.0004417732,0.0002438721,0.0001598603,0.0001141619],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001226291,"about_ca_system_score_gemma":0.0001435704,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001135972,"about_ca_topic_score_gemma":0.003483317,"domain_scores_codex":[0.9998683,0.00004056557,0.00001283389,0.00004436135,0.00001935475,0.00001455898],"domain_scores_gemma":[0.9996027,0.0001775904,0.0001161168,0.00003469973,0.00004021372,0.00002876723],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009238192,0.0001996575,0.6468076,0.0002737779,0.0004865967,0.0006690242,0.0006219249,0.005574801,0.1765393,0.001167249,0.0009157379,0.1658206],"study_design_scores_gemma":[0.0000187851,0.0005287674,0.9648081,0.00002462374,0.00009881182,0.00103423,0.0002131597,0.02175981,0.008936134,0.002102578,0.0004436694,0.00003131394],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9861324,0.0002692609,0.01226599,0.0001013804,0.00000705281,0.00003113805,0.0004076953,0.00007898008,0.0007060061],"genre_scores_gemma":[0.9942967,0.0001433467,0.005156463,0.00001669709,0.00001124212,0.00001768835,0.0002725665,0.000005248083,0.00007996936],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001135972,"threshold_uncertainty_score":0.002322793,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1179283550407679,"score_gpt":0.3208411636767886,"score_spread":0.2029128086360207,"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."}}