{"id":"W4220852416","doi":"10.1162/netn_a_00236","title":"Benchmarking functional connectivity by the structure and geometry of the human brain","year":2022,"lang":"en","type":"article","venue":"Network Neuroscience","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Functional connectivity; Functional organization; Embedding; Neuroscience; Computer science; Functional integration; Hierarchy; Artificial intelligence; Biology; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":["sts"],"consensus_categories":[],"category_scores_codex":[0.0007113709,0.0001612317,0.0001551933,0.00004442716,0.004181203,0.00006217475,0.00064677,0.00002557055,0.000093623],"category_scores_gemma":[0.003274268,0.0001064628,0.00006929382,0.00154458,0.001071848,0.0001558382,0.001282483,0.0005612255,3.186885e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005199173,"about_ca_system_score_gemma":0.00005240957,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002369195,"about_ca_topic_score_gemma":0.00002025082,"domain_scores_codex":[0.9972425,0.0006446924,0.0001883946,0.0006796097,0.0008877573,0.0003570436],"domain_scores_gemma":[0.9941552,0.005157643,0.0002080089,0.0004101051,0.0000270464,0.00004205611],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00002454,0.00005915292,0.05728537,0.000008193999,0.000003084577,0.000002503871,0.0001319386,0.0228624,0.8287331,0.01125046,0.07866028,0.0009789839],"study_design_scores_gemma":[0.000619574,0.0004683225,0.8605888,0.00001407934,0.00002222544,0.0003527204,0.0001260616,0.007929351,0.03345303,0.01167833,0.0843,0.0004475446],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9884344,0.00009382294,0.0001613901,0.008363698,0.002256626,0.0002889445,0.00008401005,0.00003498851,0.0002821355],"genre_scores_gemma":[0.9823096,0.000003702657,0.000005827419,0.01709807,0.0001848819,0.00002102104,8.119897e-7,0.00001182132,0.0003642373],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8033034,"threshold_uncertainty_score":0.9971152,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02716091869610945,"score_gpt":0.2428626720849885,"score_spread":0.2157017533888791,"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."}}