{"id":"W2460109857","doi":"10.3389/fnins.2016.00313","title":"Systemic Low-Frequency Oscillations in BOLD Signal Vary with Tissue Type","year":2016,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"National Institutes of Health; National Institute on Drug Abuse; Türkiye Bilimsel ve Teknolojik Araştırma Kurumu","keywords":"Voxel; Resting state fMRI; Blood-oxygen-level dependent; Functional magnetic resonance imaging; SIGNAL (programming language); Amplitude; Neuroscience; Nuclear magnetic resonance; Magnetic resonance imaging; Oscillation (cell signaling); Physics; Psychology; Computer science; Medicine; Biology; Artificial intelligence; Optics; Radiology","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":[],"consensus_categories":[],"category_scores_codex":[0.0003038022,0.0002039469,0.00024568,0.0004293438,0.0001902716,0.00004596681,0.000503469,0.00005591559,0.00001492062],"category_scores_gemma":[0.003975669,0.0001448847,0.00002353322,0.001944593,0.0005793405,0.0006722902,0.0001191004,0.000184117,0.00003170428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000231295,"about_ca_system_score_gemma":0.0001810244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002288946,"about_ca_topic_score_gemma":0.00004328044,"domain_scores_codex":[0.9975173,0.0002023577,0.0002798015,0.0009593268,0.0005314266,0.0005097972],"domain_scores_gemma":[0.998436,0.0009650654,0.00009985674,0.0003650071,0.00004796475,0.00008605303],"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":[0.00006975486,0.00009802225,0.1483814,0.00002248044,8.103514e-7,0.0001791127,0.0001520485,0.0007098058,0.8448386,0.001171866,0.00276961,0.001606545],"study_design_scores_gemma":[0.007086342,0.00366553,0.5314018,0.00240223,0.00003301875,0.001240968,0.0005959944,0.01136344,0.4012257,0.01798175,0.01956187,0.003441377],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.959887,0.0002310774,0.02418066,0.005142942,0.005173628,0.0009115846,0.00004011008,0.0002028891,0.004230145],"genre_scores_gemma":[0.9967928,0.00008043314,0.0007023443,0.00140576,0.00004860819,0.00004306607,1.875766e-7,0.00002025261,0.0009065377],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4436129,"threshold_uncertainty_score":0.5908226,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02176131346079861,"score_gpt":0.2396398377477382,"score_spread":0.2178785242869396,"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."}}