{"id":"W2479037164","doi":"10.17925/enr.2011.06.03.161","title":"Advances in the Role of Neuroimaging to Monitor Disease Progression in Parkinson’s Disease","year":2011,"lang":"en","type":"article","venue":"European Neurological Review","topic":"Parkinson's Disease Mechanisms and Treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institutes of Health Research; Fondation pour la Recherche sur Alzheimer; Michael Smith Health Research BC; Teva Pharmaceutical Industries","keywords":"Positron emission tomography; Neuroimaging; Medicine; Parkinson's disease; Neuroscience; Functional imaging; Dopaminergic; Putamen; Biomarker; Disease; Functional neuroimaging; Emission computed tomography; Imaging biomarker; Cerebral blood flow; Pet imaging; Dopamine; Pathology; Internal medicine; Magnetic resonance imaging; Psychology; Radiology; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004200737,0.0002053133,0.0003530489,0.00007987524,0.0000309168,0.000007913508,0.0002765905,0.00001159626,0.0000614673],"category_scores_gemma":[0.0005367783,0.0001148154,0.0001373288,0.0003442257,0.00004852244,0.00008691572,0.0001182802,0.0001936876,0.00008210372],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009817115,"about_ca_system_score_gemma":0.0000208266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002201577,"about_ca_topic_score_gemma":6.475481e-7,"domain_scores_codex":[0.9977418,0.0008092091,0.0003948938,0.0004608388,0.0003078142,0.0002854919],"domain_scores_gemma":[0.9989352,0.00005708089,0.0001079239,0.0004646057,0.00002608635,0.0004090611],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001130815,0.001770477,0.5269652,0.0007718195,0.000004443351,0.007321129,0.00008181681,0.00000185629,0.0000488955,0.0002295682,0.00005702851,0.4616169],"study_design_scores_gemma":[0.0004018172,0.0003585348,0.8405443,0.001655362,0.00008577798,0.000007216812,0.000005240915,0.00003365888,0.000009027931,0.0002853402,0.1565239,0.00008975867],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.697437,0.2881833,0.00001155399,0.002294552,0.00009173316,0.00249014,0.00002123858,0.00006736883,0.009403083],"genre_scores_gemma":[0.9484763,0.04603675,0.0001694308,0.005137139,0.00003516781,0.0001086349,0.000007358477,0.00002187457,0.000007392737],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4615272,"threshold_uncertainty_score":0.4682036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03543105239047502,"score_gpt":0.3108085070481553,"score_spread":0.2753774546576803,"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."}}