{"id":"W2980479599","doi":"10.1016/j.exger.2019.110748","title":"Default mode network and the timed up and go in MCI: A structural covariance analysis","year":2019,"lang":"en","type":"article","venue":"Experimental Gerontology","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University Health Centre; University Health Network; McGill University; Jewish General Hospital; Université de Montréal; Institut Universitaire de Gériatrie de Montréal","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Default mode network; Covariance; Econometrics; Psychology; Economics; Neuroscience; Statistics; Mathematics; Functional connectivity","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":[0.0002007997,0.0001216918,0.000385596,0.00007537894,0.00005708767,0.00002125876,0.00006193035,0.0000638037,0.0006348291],"category_scores_gemma":[0.00001555913,0.00008128597,0.00005546674,0.0001974081,0.0002804198,0.00006200064,0.0001026836,0.0001459979,0.00002146576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004315236,"about_ca_system_score_gemma":0.00002321153,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004775707,"about_ca_topic_score_gemma":0.0002226596,"domain_scores_codex":[0.998898,0.000156046,0.000177315,0.0002926411,0.0001529715,0.0003230692],"domain_scores_gemma":[0.9995937,0.0001005373,0.00004033346,0.0001642175,0.0000221669,0.0000790738],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004086617,0.00008422395,0.9768211,0.00002409108,0.0008330267,0.00005355387,0.003406442,0.00004202533,0.007878861,0.003683678,0.0003435336,0.002742889],"study_design_scores_gemma":[0.0161087,0.0005960524,0.9441591,0.00002457034,0.0002798287,0.0001483732,0.002389328,0.03214101,0.003048321,0.0004826593,0.0004184606,0.0002035757],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9909174,0.004192418,0.00009330541,0.0005849357,0.00009947419,0.0005695091,0.000002072216,0.00001170494,0.003529126],"genre_scores_gemma":[0.9970264,0.00003973497,0.0003194315,0.000500461,0.00003988449,0.00006132533,0.00001760163,0.000007403609,0.00198771],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03266194,"threshold_uncertainty_score":0.6950933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01598450302326896,"score_gpt":0.3483433557417263,"score_spread":0.3323588527184573,"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."}}