{"id":"W3107070876","doi":"10.1101/2020.11.29.402750","title":"Investigating the effects of healthy cognitive aging on brain functional connectivity using 4.7 T resting-state functional Magnetic Resonance Imaging","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Women and Children’s Health Research Institute; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Resting state fMRI; Functional magnetic resonance imaging; Cognition; Neuroscience; Magnetic resonance imaging; Psychology; Functional connectivity; Blood-oxygen-level dependent; Audiology; Medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.0004708121,0.0003414049,0.0001838431,0.0005494687,0.0001461467,0.0002742527,0.0001907993,0.0002545175,0.001153187],"category_scores_gemma":[0.0008808341,0.0001085945,0.0002081514,0.0002308406,0.0002208564,0.0002799493,0.0002209718,0.0001330067,0.0001227903],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000134814,"about_ca_system_score_gemma":0.0001656341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001648579,"about_ca_topic_score_gemma":0.003536526,"domain_scores_codex":[0.9999163,0.000019511,0.000007549314,0.00003103646,0.00001233598,0.00001336336],"domain_scores_gemma":[0.9997608,0.00007216673,0.00006810419,0.00003203571,0.00004676458,0.0000202528],"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":[0.001510718,0.0002972241,0.2754704,0.0005517432,0.000968152,0.0007939251,0.0009561562,0.006938921,0.5572673,0.001505675,0.002323707,0.151416],"study_design_scores_gemma":[0.00002396763,0.0005141227,0.9569635,0.00002171331,0.0002691236,0.0005702875,0.0001294382,0.009075887,0.02906496,0.002054055,0.001285852,0.00002701016],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9899349,0.0005599917,0.007971523,0.00006492126,0.00001009162,0.00002536852,0.0006261184,0.00007887684,0.0007280866],"genre_scores_gemma":[0.9945924,0.0002108932,0.004379987,0.00002767177,0.00001434682,0.00003846423,0.0004023065,0.00001130204,0.0003226338],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001648579,"threshold_uncertainty_score":0.003857851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04081884511799552,"score_gpt":0.2545169379569785,"score_spread":0.213698092838983,"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."}}