{"id":"W2885022815","doi":"10.1186/s13195-018-0402-y","title":"In vivo quantification of neurofibrillary tangles with [18F]MK-6240","year":2018,"lang":"en","type":"article","venue":"Alzheimer s Research & Therapy","topic":"Alzheimer's disease research and treatments","field":"Medicine","cited_by":196,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre; Douglas Mental Health University Institute; McGill University; Montreal Neurological Institute and Hospital","funders":"Fonds de Recherche du Québec - Santé; Alzheimer Society Research Program; Canadian Institutes of Health Research; Alzheimer Society; Weston Brain Institute; Consortium canadien en neurodégénérescence associée au vieillissement; Alzheimer's Association","keywords":"In vivo; Neurology; Magnetic resonance imaging; Positron emission tomography; Binding potential; Pathology; Nuclear medicine; Alzheimer's disease; Medicine; Neuroimaging; Neuroscience; Chemistry; Biology; Disease; Radiology","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0007771579,0.0002110364,0.0003685112,0.0005808295,0.0001585697,0.00003620739,0.0002079672,0.00008251382,0.0007265447],"category_scores_gemma":[0.00006472475,0.0001501169,0.00009033605,0.001233568,0.0009755172,0.0002473099,0.00006541351,0.0003053127,0.000211931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004523824,"about_ca_system_score_gemma":0.0005279396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007523032,"about_ca_topic_score_gemma":0.00006251036,"domain_scores_codex":[0.9966035,0.0004065084,0.000323473,0.0005181232,0.001394349,0.0007540622],"domain_scores_gemma":[0.9975989,0.0002523962,0.00007157469,0.0008327491,0.000870611,0.000373803],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0637143,0.01213888,0.387868,0.000274772,0.05933205,0.004321023,0.004390987,0.000009547441,0.3078613,0.005793087,0.05095631,0.1033397],"study_design_scores_gemma":[0.009807853,0.01193218,0.1279809,0.0003237989,0.0003296238,0.0001815676,0.0006184387,0.0003207821,0.8167996,0.001197669,0.0300461,0.0004615325],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9517983,0.03534085,0.00002541754,0.002367261,0.00006570019,0.001960448,0.00003670147,0.00005494144,0.008350443],"genre_scores_gemma":[0.9966858,0.00232324,0.0002720231,0.0001453985,0.0002149028,0.0001193355,0.0000262343,0.00005898318,0.0001540896],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5089383,"threshold_uncertainty_score":0.7955155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1328889846085734,"score_gpt":0.4163449334955353,"score_spread":0.2834559488869619,"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."}}