{"id":"W2802543223","doi":"","title":"Cerebral Gray Matter Volume Losses in Essential Tremor: A Case-Control Study Using High Resolution Tissue Probability Maps","year":2018,"lang":"en","type":"book-chapter","venue":"Author eBooks","topic":"Neurological disorders and treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Statistical parametric mapping; Voxel; Magnetic resonance imaging; Insula; Cerebellum; Neuroimaging; Atrophy; Voxel-based morphometry; Segmentation; Cerebrum; Psychology; Nuclear medicine; Neuroscience; White matter; Medicine; Computer science; Artificial intelligence; Pathology; Radiology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001716706,0.0005480411,0.0005298611,0.001990081,0.0007001581,0.0006494527,0.0004679811,0.0006989757,0.001520157],"category_scores_gemma":[0.003062977,0.0004766097,0.000415765,0.0008393836,0.0008034885,0.000500447,0.0005089486,0.0002821083,0.0002037104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000285244,"about_ca_system_score_gemma":0.0001530138,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002663118,"about_ca_topic_score_gemma":0.002463048,"domain_scores_codex":[0.9988845,0.0002777066,0.0001245023,0.0004435499,0.0002075926,0.00006212372],"domain_scores_gemma":[0.9987883,0.0004967208,0.000269278,0.000208933,0.000140012,0.00009675039],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002302305,0.0011163,0.958469,0.0001137283,0.0006151831,0.007560011,0.001464207,0.0003690528,0.01403682,0.0002047346,0.0002729481,0.01347563],"study_design_scores_gemma":[0.0001051967,0.001009034,0.9878743,0.00001050397,0.000203048,0.008158564,0.000192165,0.0008258316,0.001173286,0.0001039763,0.0003252245,0.00001866668],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986872,0.0001729892,0.0007790116,0.00001262462,0.000003243507,0.00005483653,0.0000665066,0.000009239653,0.0002144154],"genre_scores_gemma":[0.9992003,0.00006312071,0.0005313642,0.000006935843,0.000008595438,0.00002234711,0.0000813967,0.000004205253,0.00008186457],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002663118,"threshold_uncertainty_score":0.00907892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03535710225379786,"score_gpt":0.2880011442656811,"score_spread":0.2526440420118832,"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."}}