{"id":"W4385457320","doi":"10.1038/s41598-023-39049-x","title":"The plasma metabolome of long COVID patients two years after infection","year":2023,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Long-Term Effects of COVID-19","field":"Medicine","cited_by":99,"is_retracted":false,"has_abstract":true,"ca_institutions":"The Metabolomics Innovation Centre; University of Alberta","funders":"Instituto Nacional de Medicina Genómica; Genome Alberta; Multiple Sclerosis International Federation; Consejo Nacional de Ciencia y Tecnología; Svenska Forskningsrådet Formas; Canadian Institutes of Health Research; Genome Canada","keywords":"Metabolome; Coronavirus disease 2019 (COVID-19); 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Virology; Medicine; Betacoronavirus; Biology; Bioinformatics; Outbreak; Metabolomics; Internal medicine; Infectious disease (medical specialty); 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001788338,0.0002782882,0.0003980265,0.000318759,0.0004108674,0.0005264254,0.0001195163,0.0004183245,0.0008796875],"category_scores_gemma":[0.0003618856,0.0001227037,0.0002329819,0.0004016652,0.0001445275,0.0001990557,0.0003748823,0.0003420581,0.0002005338],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000273894,"about_ca_system_score_gemma":0.0001627291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001329207,"about_ca_topic_score_gemma":0.001617531,"domain_scores_codex":[0.9998744,0.00001784314,0.00001114746,0.00004120778,0.00002172549,0.00003373631],"domain_scores_gemma":[0.9998512,0.00001815771,0.00005884495,0.0000112435,0.000027087,0.00003338546],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.006948889,0.0002544684,0.9033808,0.0001387367,0.0002259401,0.002019148,0.0004861914,0.0001637562,0.06656614,0.00005575842,0.0005911601,0.01916908],"study_design_scores_gemma":[0.00002483779,0.00104958,0.992934,0.00001578267,0.00007039343,0.001276858,0.000334185,0.0001962976,0.002947015,0.00003170001,0.00110923,0.00001013702],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983248,0.0007098259,0.0001316482,0.00004509239,0.000009936735,0.00001096848,0.0005207428,0.000006427317,0.0002405543],"genre_scores_gemma":[0.9974382,0.0004177533,0.0002744112,0.0001162303,0.0000193965,0.000024152,0.001167235,0.00000347018,0.0005392607],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001329207,"threshold_uncertainty_score":0.002942801,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01074298371371421,"score_gpt":0.2937010079880981,"score_spread":0.2829580242743839,"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."}}