{"id":"W2902815278","doi":"10.1089/brain.2017.0576","title":"Multimodal Brain Parcellation Based on Functional and Anatomical Connectivity","year":2018,"lang":"en","type":"article","venue":"Brain Connectivity","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Artificial intelligence; Human Connectome Project; Neuroimaging; Voxel; Pattern recognition (psychology); Weighting; Connectome; Functional magnetic resonance imaging; Dimensionality reduction; Functional connectivity; Machine learning; 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":[0.001532367,0.000845672,0.0006481249,0.002812817,0.0006537096,0.001897799,0.0005943706,0.000652609,0.003543269],"category_scores_gemma":[0.007450284,0.0002891669,0.0006860734,0.001927901,0.0009149623,0.002065139,0.00138649,0.0006765202,0.0007501614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005217424,"about_ca_system_score_gemma":0.0004162893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00216544,"about_ca_topic_score_gemma":0.004963622,"domain_scores_codex":[0.999173,0.0002569687,0.00004062079,0.000304769,0.0001490751,0.00007549723],"domain_scores_gemma":[0.9973211,0.001083526,0.0004093377,0.0007355126,0.0003656888,0.00008487213],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0008860384,0.0001414296,0.0371505,0.0007159957,0.0007474195,0.0006712851,0.002404779,0.06488174,0.2436118,0.02007716,0.006744409,0.6219674],"study_design_scores_gemma":[0.0000713616,0.0004186562,0.2421399,0.0001430695,0.0006240857,0.001952333,0.001423703,0.525196,0.115337,0.0898617,0.02257577,0.0002565119],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1742205,0.0004705266,0.8185992,0.0002383696,0.00003363069,0.000227944,0.001007512,0.001539981,0.003662372],"genre_scores_gemma":[0.6891626,0.0005233999,0.3057915,0.00008627957,0.0000806926,0.0004544605,0.00194022,0.0006816075,0.001279197],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003543269,"threshold_uncertainty_score":0.0118534,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03862207954109014,"score_gpt":0.2764754412057229,"score_spread":0.2378533616646327,"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."}}