{"id":"W7064699414","doi":"","title":"Clinical and multimodal biomarker correlates of ADNI neuropathological findings","year":2013,"lang":"en","type":"article","venue":"Digital Commons@Becker (Washington University School of Medicine)","topic":"Power Transformer Diagnostics and Insulation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; University of California, Los Angeles; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; Eli Lilly and Company; Medpace; Biogen; University of California, San Diego; BioClinica; Synarc; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association","keywords":"Biomarker; Disease; Clinical neurology; MEDLINE","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":[0.0001998537,0.0001766558,0.0003905927,0.0001842302,0.00004454234,0.00002360577,0.0002276555,0.0001562202,0.0001250695],"category_scores_gemma":[0.0004096272,0.0001599466,0.00008949732,0.0002086992,0.0005482196,0.0006633896,0.00007828463,0.0003124154,0.00002923962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002168816,"about_ca_system_score_gemma":0.00001636074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007167468,"about_ca_topic_score_gemma":0.000005198667,"domain_scores_codex":[0.998928,0.00004232514,0.0004311939,0.0001918308,0.0002128676,0.0001938389],"domain_scores_gemma":[0.9989274,0.0004644056,0.00007367558,0.0001926953,0.0001146475,0.0002271463],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005069298,0.00008988773,0.9850652,0.00007407792,0.00006669657,0.00002054513,0.0002073725,0.00008244551,0.0009743982,0.0004777214,0.003681408,0.009209591],"study_design_scores_gemma":[0.001542633,0.0002608407,0.9864436,0.0001781534,0.00005330296,0.000009078763,0.000352639,0.008528044,0.0001156074,0.0002443696,0.002094963,0.0001767861],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9872627,0.0001404219,0.001239331,0.0002195516,0.0002323833,0.0002001149,0.00004029123,0.00008524587,0.01057994],"genre_scores_gemma":[0.9994247,0.0001856137,0.0002249631,0.00003165473,0.00002228414,3.976297e-7,0.00003478504,0.00001576545,0.00005981335],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.012162,"threshold_uncertainty_score":0.6522435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01707782939460434,"score_gpt":0.2270924063572922,"score_spread":0.2100145769626879,"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."}}