{"id":"W2966191040","doi":"10.1016/j.jalz.2019.05.006","title":"Frequency and longitudinal clinical outcomes of Alzheimer's AT(N) biomarker profiles: A longitudinal study","year":2019,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":80,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Aging; Canadian Institutes of Health Research; National Institutes of Health; U.S. Department of Defense; Fudan University; Science and Technology Commission of Shanghai Municipality; National Institute of Biomedical Imaging and Bioengineering; Northern California Institute for Research and Education; National Natural Science Foundation of China","keywords":"Hazard ratio; Proportional hazards model; Biomarker; Internal medicine; Longitudinal study; Dementia; Clinical trial; Neurodegeneration; Medicine; Multivariate statistics; Oncology; Disease; Multivariate analysis; Psychology; Pathology; Confidence interval; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006019357,0.0003518149,0.0003408822,0.0008195821,0.0006247277,0.0007640517,0.0005387759,0.0006492563,0.001159736],"category_scores_gemma":[0.008550586,0.0002359429,0.0006554245,0.000969611,0.0003706091,0.0009885781,0.0006342799,0.0006225102,0.0002504364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003902532,"about_ca_system_score_gemma":0.0005551054,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002429918,"about_ca_topic_score_gemma":0.002575822,"domain_scores_codex":[0.9983012,0.0008232568,0.0001601216,0.0003894667,0.0002011345,0.0001249267],"domain_scores_gemma":[0.9939224,0.001056925,0.00327052,0.0006171539,0.0006782199,0.0004548225],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005087021,0.0001071731,0.9960556,0.00001930885,0.0001934061,0.00001581927,0.00009359064,0.00005341144,0.0002273599,0.00005092353,0.00007206231,0.002602634],"study_design_scores_gemma":[0.00003748092,0.0007892093,0.9975896,0.00002140371,0.0001708388,0.0001616131,0.00009971432,0.0004443937,0.0002036894,0.0002017463,0.0002698984,0.00001034293],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975194,0.0003613599,0.001114303,0.00009210213,0.000009765015,0.00003979226,0.000536826,0.000006924928,0.0003195476],"genre_scores_gemma":[0.9982293,0.00009730874,0.0009145994,0.00005349315,0.0000201853,0.0000704643,0.0004455988,0.000002383577,0.0001667477],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006019357,"threshold_uncertainty_score":0.03183377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09211728561449359,"score_gpt":0.3940415740100955,"score_spread":0.3019242883956019,"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."}}