{"id":"W2945458022","doi":"10.1002/acn3.782","title":"Predicting long‐term clinical stability in amyloid‐positive subjects by <scp>FDG</scp>‐<scp>PET</scp>","year":2019,"lang":"en","type":"article","venue":"Annals of Clinical and Translational Neurology","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Aging; Canadian Institutes of Health Research; FP7 Health; Genentech; IXICO; National Institutes of Health; H. Lundbeck A/S; Pfizer; Novartis Pharmaceuticals Corporation; Ministero della Salute; Northern California Institute for Research and Education; University of Southern California; Meso Scale Diagnostics; Servier","keywords":"Neuropathology; Medicine; Neurodegeneration; Biomarker; Clinical trial; Internal medicine; Pet imaging; Disease; Oncology; Amyloid (mycology); Alzheimer's disease; Positron emission tomography; Pathology; Nuclear medicine; 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":[0.003127483,0.0002403308,0.0009571845,0.0001403715,0.00005509532,0.00001746374,0.0001573976,0.0003221943,0.0001116476],"category_scores_gemma":[0.002851931,0.0002113721,0.0003756895,0.0002380565,0.000752177,0.0001803514,0.00007548851,0.001148349,0.00004115421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001011773,"about_ca_system_score_gemma":0.0002261008,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002829357,"about_ca_topic_score_gemma":0.00004763371,"domain_scores_codex":[0.9953001,0.001018954,0.00169567,0.0008107215,0.0005943296,0.0005802289],"domain_scores_gemma":[0.9861825,0.01249616,0.0002788745,0.0002485083,0.000400949,0.0003930328],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006931528,0.001665284,0.9921797,0.0001235428,0.0001797861,0.00009927895,0.0000987,0.000002230378,0.0001683125,0.0001282093,0.0003014196,0.004360421],"study_design_scores_gemma":[0.005227425,0.004030827,0.9872337,0.0000564309,0.00006787453,0.00003525814,0.0000315598,0.0004441249,0.0007886943,0.001100694,0.0009406713,0.0000427521],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9895767,0.0004478711,0.00005776397,0.003519341,0.0002430307,0.0008513138,0.000125752,0.00002809535,0.005150107],"genre_scores_gemma":[0.994598,0.000813739,0.00003858218,0.003827069,0.0002012428,0.0000192618,0.0001537983,0.00002230489,0.0003260571],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01147721,"threshold_uncertainty_score":0.8619503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08459939832062711,"score_gpt":0.4148415460410492,"score_spread":0.3302421477204221,"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."}}