{"id":"W4220736408","doi":"10.1038/s41598-022-09506-0","title":"Multivariate genomic and transcriptomic determinants of imaging-derived personalized therapeutic needs in Parkinson’s disease","year":2022,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Parkinson's Disease Mechanisms and Treatments","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre; McGill University; Montreal Neurological Institute and Hospital","funders":"Weston Brain Institute; Health Canada; Canada First Research Excellence Fund; Canada Research Chairs; Fondation Brain Canada; McGill University; Fonds de Recherche du Québec - Santé; Michael J. Fox Foundation for Parkinson's Research","keywords":"Neuroimaging; Disease; Transcriptome; Personalized medicine; Dopaminergic; Parkinson's disease; Bioinformatics; Psychological intervention; Imaging genetics; Medicine; Biology; Computational biology; Neuroscience; Psychology; Genetics; Internal medicine; Psychiatry; Gene","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":[0.0006998035,0.0002026827,0.0002537673,0.0005003254,0.0001369846,0.00038939,0.0001067236,0.0001929276,0.0009135176],"category_scores_gemma":[0.002396824,0.00007898763,0.0002711327,0.0004994475,0.0003131247,0.0002359286,0.0002874863,0.0003100073,0.00008544626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001747843,"about_ca_system_score_gemma":0.0001802587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007637267,"about_ca_topic_score_gemma":0.001059192,"domain_scores_codex":[0.9996381,0.0001571684,0.00002599255,0.00008879584,0.00005001396,0.0000399334],"domain_scores_gemma":[0.9987942,0.0006201195,0.0003492143,0.0001034714,0.00006703591,0.00006594125],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00120099,0.0001054995,0.9371979,0.00005203889,0.0003007169,0.0002667868,0.0003471721,0.003299878,0.02741327,0.0003217293,0.0001713476,0.02932277],"study_design_scores_gemma":[0.000004445702,0.00009668552,0.9942377,0.000003401389,0.00006120998,0.0001899836,0.000135867,0.003308685,0.001227714,0.0005824664,0.0001443852,0.000007599372],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979641,0.0001316941,0.001454043,0.00003885617,0.000001492003,0.000003623019,0.0002443167,0.000007902638,0.0001539577],"genre_scores_gemma":[0.9993441,0.00002490498,0.0004143007,0.000006880889,0.00000213365,0.000003734872,0.0001502186,0.000002814141,0.00005091586],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009135176,"threshold_uncertainty_score":0.003700972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01936501981157988,"score_gpt":0.2677477325394531,"score_spread":0.2483827127278732,"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."}}