{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0002444636,0.0001295533,0.0001375425,0.0009508641,0.0002735115,0.00009557552,0.000170953,0.00006223463,0.00006376086],"category_scores_gemma":[0.02433564,0.000127582,0.00007341737,0.002572317,0.00005507321,0.0002523782,0.00006967563,0.00007189842,0.00009434558],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009538372,"about_ca_system_score_gemma":0.00008121885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000275104,"about_ca_topic_score_gemma":0.000003158131,"domain_scores_codex":[0.9986918,0.00004088712,0.0001948928,0.0004123676,0.0003585491,0.0003014916],"domain_scores_gemma":[0.9926858,0.006850304,0.00009275138,0.0001561649,0.0001539422,0.00006104377],"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":[0.00002747149,0.000262372,0.001317567,0.00007511351,0.00002688921,0.000001337395,0.0002946261,0.0006955139,0.7287614,0.04448969,0.2122019,0.01184606],"study_design_scores_gemma":[0.0006457662,0.0002890097,0.01261049,0.000005793388,0.000007181565,0.000006625541,0.00002029436,0.9238498,0.006781485,0.04446451,0.0110171,0.0003018928],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1137751,0.0001142449,0.8491791,0.03359945,0.0005388007,0.001231211,0.0001489268,0.0002275981,0.001185474],"genre_scores_gemma":[0.9632338,0.000007132671,0.0280016,0.005547157,0.0001682027,0.0002854669,0.00001449891,0.00002383856,0.002718357],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9231544,"threshold_uncertainty_score":0.9838828,"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."}}