{"id":"W2151270078","doi":"10.1002/mds.22635","title":"Mapping preclinical compensation in Parkinson's disease: An imaging genomics approach","year":2009,"lang":"en","type":"review","venue":"Movement Disorders","topic":"Parkinson's Disease Mechanisms and Treatments","field":"Medicine","cited_by":74,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Volkswagen Foundation; Hermann und Lilly Schilling-Stiftung für Medizinische Forschung","keywords":"Parkin; Neuroscience; Functional magnetic resonance imaging; PINK1; Supplementary motor area; Parkinson's disease; Psychology; Parkinsonism; Medicine; Biology; Disease; Pathology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003624458,0.0006546275,0.001568937,0.0004646078,0.0001028809,0.00006973368,0.0002393751,0.0001718078,0.00006134069],"category_scores_gemma":[0.00003532166,0.0005924737,0.0005724925,0.0003595691,0.00005095191,0.0001416273,0.00008040463,0.000380433,0.00003342325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000735777,"about_ca_system_score_gemma":0.0004065639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006012309,"about_ca_topic_score_gemma":0.00002549925,"domain_scores_codex":[0.9968171,0.0002223497,0.0008852766,0.001067109,0.0004466499,0.0005615441],"domain_scores_gemma":[0.9983698,0.0000435614,0.0003623464,0.0007301216,0.00002787184,0.0004662843],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005727231,0.002181566,0.004854506,0.003788361,0.000188688,0.00007213277,0.0000693066,0.00001517881,1.995238e-7,0.0001410859,0.0002015778,0.9884301],"study_design_scores_gemma":[0.001888028,0.00009891584,0.01647678,0.003151034,0.0009156431,0.000001079116,0.0001344871,0.001744502,8.273044e-8,0.002701239,0.9723339,0.0005543029],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0004485925,0.9936936,0.0008819711,0.0001923146,0.0001339611,0.003069171,0.00008973783,0.0001100957,0.001380477],"genre_scores_gemma":[0.001185224,0.991897,0.00166,0.001236377,0.0001276623,0.0004663734,0.003199372,0.0001013462,0.0001266013],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9878758,"threshold_uncertainty_score":0.9996527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05463779696328381,"score_gpt":0.3367840827517826,"score_spread":0.2821462857884988,"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."}}