{"id":"W4412918713","doi":"10.7554/elife.101327.3","title":"A SMARTTR workflow for multi-ensemble atlas mapping and brain-wide network analysis","year":2025,"lang":"en","type":"article","venue":"eLife","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Columbia College","funders":"National Institute of Neurological Disorders and Stroke; National Institute of General Medical Sciences; National Institute on Aging","keywords":"Workflow; Atlas (anatomy); Computer science; Brain atlas; Data science; Computational biology; Cartography; Biology; Artificial intelligence; Geography; Database","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":[0.003572668,0.002166661,0.001648021,0.002475127,0.001165367,0.0035174,0.002442014,0.001079217,0.04304553],"category_scores_gemma":[0.007252763,0.001458255,0.002929881,0.001814181,0.0005514401,0.001573753,0.003273875,0.003602726,0.02112153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008162899,"about_ca_system_score_gemma":0.003161801,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005639761,"about_ca_topic_score_gemma":0.01284685,"domain_scores_codex":[0.9987986,0.0002217208,0.0001621618,0.0004482712,0.0002767392,0.00009246224],"domain_scores_gemma":[0.9980241,0.0007374708,0.0001978335,0.0006067137,0.0003141154,0.0001198019],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007998973,0.0002035638,0.006896927,0.002750523,0.001703177,0.001210216,0.002003049,0.03731552,0.06175949,0.04745707,0.5370299,0.3008707],"study_design_scores_gemma":[0.0003967242,0.0002039028,0.00964848,0.0004107621,0.0004110015,0.001205864,0.000618014,0.2432619,0.04906968,0.1645913,0.5297462,0.000436257],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002683625,0.0002049921,0.785946,0.0002185264,0.0001802135,0.0003611081,0.0428822,0.1651393,0.002383924],"genre_scores_gemma":[0.02713736,0.0004585264,0.8466057,0.0003749541,0.00008872849,0.003264271,0.08171007,0.03570844,0.004651912],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04304553,"threshold_uncertainty_score":0.1440016,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05272760105049307,"score_gpt":0.2966929265359219,"score_spread":0.2439653254854288,"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."}}