{"id":"W1536343953","doi":"10.1111/biom.12126","title":"A variational Bayes spatiotemporal model for electromagnetic brain mapping","year":2013,"lang":"en","type":"article","venue":"Biometrics","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Down Syndrome Research Foundation; Simon Fraser University; University of Victoria","funders":"","keywords":"Bayes' theorem; Computer science; Artificial intelligence; Bayesian probability; Machine learning; Statistical physics; Physics","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":[0.003722525,0.0008064482,0.001213054,0.0009142591,0.0005242649,0.001604145,0.002564935,0.002089689,0.004266717],"category_scores_gemma":[0.008769296,0.0009785515,0.001381584,0.0009573153,0.001728896,0.002144888,0.001690344,0.001663388,0.000573592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001862567,"about_ca_system_score_gemma":0.001672121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01319495,"about_ca_topic_score_gemma":0.009023506,"domain_scores_codex":[0.99884,0.0005929972,0.00005081899,0.0002139331,0.0002182543,0.00008396272],"domain_scores_gemma":[0.997331,0.001991694,0.0001706584,0.0001122112,0.0002932974,0.0001011155],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003796847,0.0000191476,0.0006641473,0.00007488592,0.00005585109,0.0001014232,0.0001337024,0.5826035,0.0007702259,0.3988055,0.001834668,0.01489896],"study_design_scores_gemma":[0.000009018654,0.00000738257,0.00009857949,0.000007996068,0.000005879401,0.00002703173,0.000008965872,0.9235993,0.0000607902,0.0750521,0.001114297,0.000008683592],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003426286,0.0003697452,0.9934102,0.000655706,0.00003969142,0.00002522406,0.0001427596,0.00006236351,0.001868037],"genre_scores_gemma":[0.4344721,0.001748292,0.5389868,0.0005819813,0.0003494626,0.0006218309,0.0009003322,0.000320364,0.0220189],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01319495,"threshold_uncertainty_score":0.0262363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07611515801776193,"score_gpt":0.2714784690518816,"score_spread":0.1953633110341196,"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."}}