{"id":"W4321611749","doi":"10.1186/s10020-023-00610-z","title":"Organ and cell-specific biomarkers of Long-COVID identified with targeted proteomics and machine learning","year":2023,"lang":"en","type":"article","venue":"Molecular Medicine","topic":"Long-Term Effects of COVID-19","field":"Medicine","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"Children’s Health Research Institute; London Health Sciences Centre; Lawson Health Research Institute; Western University","funders":"London Community Foundation; London Health Sciences Foundation; Academic Medical Organization of Southwestern Ontario; London Health Sciences Centre","keywords":"Proteomics; Coronavirus disease 2019 (COVID-19); Molecular medicine; Computational biology; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Cell; Biology; Human genetics; Medicine; Bioinformatics; Virology; Infectious disease (medical specialty); Pathology; Disease; Cell cycle; Genetics","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":[0.0006742293,0.0002682969,0.000553528,0.0004600758,0.00009004698,0.00001537986,0.00009962129,0.0001090077,0.00007090096],"category_scores_gemma":[0.0006583676,0.0001976507,0.00003861971,0.0007646309,0.0004681676,0.00005739824,0.0001039698,0.00028999,0.000008454464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004411913,"about_ca_system_score_gemma":0.0000919427,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001294078,"about_ca_topic_score_gemma":0.00000889637,"domain_scores_codex":[0.9982204,0.0001224567,0.0003390733,0.0004728779,0.0005248057,0.0003204018],"domain_scores_gemma":[0.9987416,0.0002276191,0.0001708657,0.0003759816,0.0001095365,0.0003743706],"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":[0.0007319979,0.00004221502,0.05441994,0.001452597,0.000183499,0.002233781,0.0008198869,0.00002221329,0.9384378,0.00003459993,0.0005959512,0.001025475],"study_design_scores_gemma":[0.02956882,0.005740014,0.3640067,0.002296077,0.001006926,0.0009365004,0.000940686,0.003120551,0.5874621,0.000244119,0.003818569,0.0008589415],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9822704,0.003852891,0.005847674,0.006336882,0.00007490189,0.001198512,0.000004358165,0.0001759559,0.0002384123],"genre_scores_gemma":[0.9969349,0.0004581684,0.001232987,0.0007259106,0.00005816163,0.00002691777,0.0001531528,0.00007415771,0.0003356705],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3509758,"threshold_uncertainty_score":0.8059961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0102288224403492,"score_gpt":0.2523948159202559,"score_spread":0.2421659934799067,"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."}}