{"id":"W3129666823","doi":"10.1089/brain.2020.0939","title":"Impaired Structural Connectivity in Parkinson's Disease Patients with Mild Cognitive Impairment: A Study Based on Probabilistic Tractography","year":2021,"lang":"en","type":"article","venue":"Brain Connectivity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"","keywords":"Tractography; Diffusion MRI; Fractional anisotropy; Connectome; Connectomics; Parkinson's disease; Neuroscience; Psychology; White matter; Magnetic resonance imaging; Artificial intelligence; Pathology; Medicine; Functional connectivity; Disease; Computer science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000541059,0.0003789997,0.0003479354,0.001202747,0.0005244626,0.0004635796,0.0002424031,0.0005141586,0.001310346],"category_scores_gemma":[0.002667439,0.0002468261,0.0003569922,0.000632461,0.0004986288,0.0005173087,0.0003623898,0.0002499545,0.0001982415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003246846,"about_ca_system_score_gemma":0.0002280005,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003367419,"about_ca_topic_score_gemma":0.003139688,"domain_scores_codex":[0.9998167,0.00004424473,0.00002274966,0.00005927786,0.00003436951,0.00002268636],"domain_scores_gemma":[0.9989944,0.0003302517,0.0003722086,0.00009184139,0.0000906932,0.0001206008],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00078379,0.0001420597,0.9916043,0.00003997298,0.0001816643,0.000940257,0.0006015745,0.0001860442,0.001319862,0.00006712517,0.0000683926,0.00406497],"study_design_scores_gemma":[0.00002809989,0.0002935622,0.997071,0.000005274524,0.00005367438,0.001568361,0.0001393675,0.0005604671,0.00008534321,0.00009502473,0.00009499184,0.000004771174],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995793,0.000090684,0.00009704565,0.00001156733,0.000001055534,0.000008904181,0.00004136703,0.000001854067,0.0001682382],"genre_scores_gemma":[0.9997948,0.00002992475,0.00007666692,0.000005369056,0.000003871127,0.000005314608,0.0000591662,0.000001038611,0.00002392905],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003367419,"threshold_uncertainty_score":0.006695628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03133652534068452,"score_gpt":0.3133172704049345,"score_spread":0.28198074506425,"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."}}