{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002154451,0.0001208792,0.0002260774,0.0003263389,0.0001936489,0.000110783,0.00008180663,0.0000560984,0.0000740533],"category_scores_gemma":[0.001852546,0.00008486307,0.0001538423,0.00108287,0.0003482792,0.0001548737,0.0001230678,0.0001218789,0.0001622567],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007910532,"about_ca_system_score_gemma":0.0002407026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008124298,"about_ca_topic_score_gemma":0.00008151773,"domain_scores_codex":[0.9977798,0.00007588105,0.0004771958,0.0004754546,0.0008756147,0.0003160749],"domain_scores_gemma":[0.9981162,0.0002398426,0.000301819,0.0009282289,0.0002308427,0.0001830993],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000951999,0.00008431209,0.9779886,0.0001201308,0.00005895914,0.001108028,0.0003069817,0.00006838658,0.002180561,0.00001526645,0.01141826,0.006555296],"study_design_scores_gemma":[0.0006554266,0.00008722053,0.9480116,0.00007831423,0.00009330489,0.00009300461,0.00001000465,0.0001050028,0.006539081,0.0007701989,0.04344649,0.0001103004],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9906145,0.00005857789,0.00002019214,0.0002740709,0.007800455,0.0007015637,0.000003031288,0.0001354471,0.0003921911],"genre_scores_gemma":[0.9956731,0.00000923475,0.00003819224,0.00007358337,0.00007568477,0.00006462572,0.0000677916,0.00002021432,0.003977612],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03202823,"threshold_uncertainty_score":0.3460616,"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."}}