{"id":"W3100652799","doi":"10.1016/j.cmpb.2020.105830","title":"Source imaging of deep-brain activity using the regional spatiotemporal Kalman filter","year":2020,"lang":"en","type":"article","venue":"Computer Methods and Programs in Biomedicine","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"Seventh Framework Programme; Deutsche Forschungsgemeinschaft","keywords":"Electroencephalography; Computer science; Ictal; Brain activity and meditation; Artificial intelligence; Kalman filter; Pattern recognition (psychology); Neuroscience; Psychology","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":[0.0003807926,0.0003666712,0.0004091347,0.0003402079,0.0001867398,0.000483456,0.0003881088,0.0003730509,0.00155578],"category_scores_gemma":[0.001509451,0.0002918566,0.0004650005,0.0006516582,0.0001752105,0.0008520144,0.0004952387,0.0006835623,0.0004267535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003763615,"about_ca_system_score_gemma":0.0008902967,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004743511,"about_ca_topic_score_gemma":0.00775507,"domain_scores_codex":[0.9998794,0.0000271284,0.000007991518,0.0000350739,0.00003890406,0.00001153608],"domain_scores_gemma":[0.9997527,0.0001065984,0.00004147083,0.00003135531,0.00005652552,0.00001133419],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003403794,0.00009423822,0.00435899,0.000323978,0.0002894981,0.0001406602,0.0002930735,0.3131842,0.1700184,0.03301167,0.00441364,0.4735312],"study_design_scores_gemma":[0.00001647006,0.00004300303,0.001845708,0.00001282786,0.00003896101,0.00008883106,0.00001631953,0.9706516,0.01759926,0.007484679,0.002178788,0.00002349295],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006348363,0.0001176621,0.9927856,0.00005663657,0.00001148998,0.00001104753,0.00009922023,0.0002727163,0.0002973564],"genre_scores_gemma":[0.2933275,0.0006937615,0.7023579,0.00008180161,0.00004273509,0.0001160846,0.0004905593,0.0002452201,0.002644365],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004743511,"threshold_uncertainty_score":0.009431839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1668231371783551,"score_gpt":0.3777524673266563,"score_spread":0.2109293301483012,"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."}}