{"id":"W2162099662","doi":"10.1109/iembs.2007.4353713","title":"A Framework for Group Analysis of fMRI Data using Dynamic Bayesian Networks","year":2007,"lang":"en","type":"article","venue":"Conference proceedings","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Dynamic Bayesian network; Computer science; Bayesian probability; Bayesian network; Group (periodic table); Group analysis; Data mining; Artificial intelligence; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0008440272,0.0001944057,0.0004156757,0.0003738124,0.0002434622,0.00008575973,0.0007163835,0.0001315186,0.0000309137],"category_scores_gemma":[0.009517246,0.0001931787,0.0001127749,0.001768549,0.000237028,0.000442818,0.0003825748,0.0002166141,0.00000102809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006661993,"about_ca_system_score_gemma":0.00004231043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000021459,"about_ca_topic_score_gemma":0.0000662383,"domain_scores_codex":[0.9980678,0.000009738765,0.0003553072,0.0008301944,0.0003045212,0.0004324673],"domain_scores_gemma":[0.995782,0.003227045,0.0002927268,0.0003402287,0.0002724174,0.00008565102],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001035488,0.0005878758,0.08026309,0.0004752669,0.001448891,0.00001066809,0.003543377,0.001156291,0.2882226,0.5930687,0.001229092,0.02895864],"study_design_scores_gemma":[0.0002147022,0.0001101695,0.009287477,0.00008714319,0.0005670337,0.000004806275,0.000647266,0.9724287,0.003004853,0.01293771,0.0004210485,0.0002891126],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1623557,0.00004748277,0.8360407,0.0005222147,0.0002090599,0.000308716,0.00005671405,0.00007035631,0.0003889794],"genre_scores_gemma":[0.9779657,0.00002163405,0.02124991,0.0006030945,0.00008382474,0.00001370827,0.00001444196,0.00002000971,0.00002766122],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9712724,"threshold_uncertainty_score":0.998826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1142384397713212,"score_gpt":0.3528320207102709,"score_spread":0.2385935809389497,"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."}}