{"id":"W4388841197","doi":"10.1101/2023.11.18.567647","title":"Mapping Cerebellar Anatomical Heterogeneity in Mental and Neurological Illnesses","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Vestibular and auditory disorders","field":"Neuroscience","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; Alzheimer's Association","keywords":"Cerebellum; Normative; Psychology; Neuroscience; Autism; Schizophrenia (object-oriented programming); Cognition; Postmortem studies; Population; Autism spectrum disorder; Voxel-based morphometry; Magnetic resonance imaging; Medicine; Psychiatry; White matter","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006489024,0.0002311591,0.0002015377,0.001075962,0.000203248,0.0005403387,0.0002064174,0.000243292,0.001348321],"category_scores_gemma":[0.002599283,0.0001774608,0.0001914789,0.0004487555,0.0005422542,0.0002755404,0.0007383403,0.0001861966,0.0001364025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003241595,"about_ca_system_score_gemma":0.0002301674,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007892041,"about_ca_topic_score_gemma":0.01251725,"domain_scores_codex":[0.9998255,0.00003999151,0.00001245525,0.00008351495,0.00002169553,0.00001677134],"domain_scores_gemma":[0.9993286,0.0001942986,0.0002315602,0.0001526292,0.00005840003,0.00003455273],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001017047,0.00004497602,0.806713,0.0002009307,0.0006187648,0.0008918114,0.002189877,0.01418401,0.1109148,0.003503947,0.001205153,0.05851575],"study_design_scores_gemma":[0.00001054058,0.00004772955,0.9830732,0.00002616437,0.00006542847,0.001100656,0.0002989126,0.007249812,0.004199424,0.002967302,0.0009426442,0.00001813013],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9936148,0.0001598286,0.005050256,0.00003883788,0.000001962174,0.000006317,0.000678203,0.00005828455,0.0003913475],"genre_scores_gemma":[0.998051,0.00003871629,0.001473906,0.000007112794,0.000001227038,0.000006199021,0.0002907236,0.00002062212,0.0001103754],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007892041,"threshold_uncertainty_score":0.01569223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03153882261643279,"score_gpt":0.2449842171999754,"score_spread":0.2134453945835426,"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."}}