{"id":"W3042402214","doi":"10.1093/brain/awaa180","title":"18F-MK-6240 PET for early and late detection of neurofibrillary tangles","year":2020,"lang":"en","type":"article","venue":"Brain","topic":"Connective tissue disorders research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":257,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Montreal Neurological Institute and Hospital; Centre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-Jean; McGill University; Douglas Mental Health University Institute","funders":"Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Cummings Foundation; Alzheimer's Association","keywords":"Neuroscience; Neurofibrillary tangle; Pathology; Biology; Medicine; Senile plaques; Alzheimer's disease; Disease","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":[0.00006578866,0.00005873942,0.00007668397,0.0000178689,0.00002960821,0.00000854334,0.00005536819,0.00002786994,0.000005080806],"category_scores_gemma":[0.0004599465,0.00006202018,0.00003761327,0.00005623968,0.00004396504,0.00000210202,0.00006452521,0.00002969029,0.000001682898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001746488,"about_ca_system_score_gemma":0.00001587335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001883123,"about_ca_topic_score_gemma":0.00002202726,"domain_scores_codex":[0.9995409,0.00003665769,0.00007436347,0.000187387,0.00005439435,0.0001063005],"domain_scores_gemma":[0.9997431,0.00003205234,0.00002615713,0.00008632863,0.00006512764,0.00004723221],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001518359,0.000004964601,0.001484451,0.00003880779,0.00001696592,0.000001998067,0.00006877589,0.00000302613,0.9867263,0.00002003099,0.0002534291,0.01122938],"study_design_scores_gemma":[0.0009248598,0.001339868,0.03552683,0.000005979809,0.000008577573,0.00001176072,0.0001175336,0.000590936,0.9115896,0.00019385,0.04954379,0.0001464764],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954143,0.0005698816,0.002283644,0.001236974,0.00001750133,0.0002127135,0.00002770387,0.000006870243,0.0002303897],"genre_scores_gemma":[0.9992995,0.00003181635,0.00009299632,0.0002630862,0.00006498599,0.00001195505,0.00001890234,0.00001381706,0.0002029496],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0751368,"threshold_uncertainty_score":0.252911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01794808892231174,"score_gpt":0.2711424266008474,"score_spread":0.2531943376785357,"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."}}