{"id":"W2761800358","doi":"10.3389/fnins.2017.00546","title":"The Effect of Low-Frequency Physiological Correction on the Reproducibility and Specificity of Resting-State fMRI Metrics: Functional Connectivity, ALFF, and ReHo","year":2017,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Resting state fMRI; Reproducibility; Functional connectivity; Default mode network; Audiology; Psychology; Neuroscience; Medicine; Statistics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.006687499,0.0007961316,0.0005571513,0.000729253,0.0004863573,0.0007207697,0.0005683592,0.0007674916,0.0006210381],"category_scores_gemma":[0.02834495,0.0003373438,0.0004984026,0.0004668781,0.0008594446,0.0005985553,0.0005353977,0.0004435354,0.0002787973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002112346,"about_ca_system_score_gemma":0.0003097869,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00126911,"about_ca_topic_score_gemma":0.002493532,"domain_scores_codex":[0.9967455,0.001609965,0.0003568873,0.0007428348,0.0004224289,0.0001223075],"domain_scores_gemma":[0.9813111,0.01306287,0.001609712,0.002446105,0.00140294,0.0001672868],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004135884,0.000266869,0.1882065,0.00088625,0.002108332,0.001211239,0.002383749,0.01270501,0.564339,0.0009644026,0.0009723133,0.2218204],"study_design_scores_gemma":[0.00009629194,0.001606697,0.8146515,0.00005151232,0.0007055457,0.002753417,0.000298032,0.03011886,0.1465715,0.001435379,0.001579962,0.0001313496],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9064177,0.001594962,0.08963574,0.0002498473,0.0001475628,0.0001137872,0.0002438551,0.0005605542,0.001035914],"genre_scores_gemma":[0.9730032,0.0002023068,0.02579916,0.00006018958,0.00004783544,0.0000784212,0.0002257843,0.0002425756,0.0003405101],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9933125,"threshold_uncertainty_score":0.03536725,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05199699132219971,"score_gpt":0.275702246768076,"score_spread":0.2237052554458763,"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."}}