{"id":"W4389173338","doi":"10.21203/rs.3.rs-3666285/v1","title":"Novel Plasma Protein Biomarkers: A Time-Dependent predictive model for Alzheimer's Disease","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Alzheimer's disease research and treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; University of California, Los Angeles; Servier; National Institute of Biomedical Imaging and Bioengineering; Nanjing Medical University; Eisai; Genentech; IXICO; National Natural Science Foundation of China; Novartis Pharmaceuticals Corporation; University of California, San Diego; BioClinica; Northern California Institute for Research and Education; F. Hoffmann-La Roche; Bristol-Myers Squibb; Eli Lilly and Company; Medpace; Biogen; Synarc; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association","keywords":"Receiver operating characteristic; Proportional hazards model; Cohort; Internal medicine; Incidence (geometry); Oncology; Disease; Biomarker; Medicine; Lasso (programming language); Alzheimer's Disease Neuroimaging Initiative; Alzheimer's disease; Psychology; Biology; Computer science","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":[0.002205566,0.0009642512,0.0008777367,0.001041296,0.0002793347,0.001404604,0.0007759025,0.0007575795,0.001119556],"category_scores_gemma":[0.003068983,0.0002564794,0.0008921241,0.0005930631,0.0003544191,0.0005321595,0.0005754171,0.001183759,0.0003803587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000606806,"about_ca_system_score_gemma":0.001179366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005107522,"about_ca_topic_score_gemma":0.002297851,"domain_scores_codex":[0.9995798,0.0001509264,0.00002594858,0.000119079,0.0000720961,0.00005213703],"domain_scores_gemma":[0.9988508,0.0006137786,0.0002250455,0.0000483266,0.000207704,0.0000543951],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008389333,0.0004677487,0.1120379,0.0001315201,0.0005259233,0.000492746,0.0001373506,0.7983636,0.004277376,0.003073149,0.003516186,0.07613754],"study_design_scores_gemma":[0.00001203196,0.00006283387,0.003119548,0.0000094302,0.00003636421,0.00004222314,0.000008012762,0.9952812,0.0002107705,0.0009718068,0.0002371124,0.000008747007],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.546908,0.002375831,0.4437006,0.002076892,0.0002088338,0.0001640488,0.001800473,0.0009599123,0.001805375],"genre_scores_gemma":[0.9753354,0.0004602009,0.02164935,0.0001015872,0.00008888713,0.0001555807,0.0007293221,0.00002489431,0.001454865],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005107522,"threshold_uncertainty_score":0.01166427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1447784839895473,"score_gpt":0.4144860942247351,"score_spread":0.2697076102351877,"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."}}