{"id":"W4391944787","doi":"10.1016/j.ebiom.2024.105023","title":"Unravelling long COVID: insights from proteomics and considerations for comprehensive understanding","year":2024,"lang":"en","type":"letter","venue":"EBioMedicine","topic":"Long-Term Effects of COVID-19","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Paul's Hospital; University of British Columbia; Prevention of Organ Failure; Providence Health Care","funders":"Canadian Institutes of Health Research","keywords":"Cohort; Scopus; Vaccination; Coronavirus disease 2019 (COVID-19); Cohort study; Medicine; MEDLINE; Longitudinal study; Gerontology; Family medicine; Psychology; Pathology; Biology; Disease; Infectious disease (medical specialty)","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":[0.0056394,0.000717658,0.001609094,0.0007748484,0.001649668,0.003366891,0.001384708,0.0138017,0.00354605],"category_scores_gemma":[0.0191803,0.0004009657,0.001008046,0.0005564064,0.003762952,0.009491261,0.001841947,0.02928561,0.00375179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003648588,"about_ca_system_score_gemma":0.002514666,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001747001,"about_ca_topic_score_gemma":0.002987708,"domain_scores_codex":[0.9964556,0.001259745,0.0005228716,0.0004262083,0.001002257,0.0003334597],"domain_scores_gemma":[0.980888,0.01184095,0.0009299639,0.0009722604,0.003644404,0.001724458],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000259223,0.0001231955,0.004939824,0.001274319,0.0001109392,0.01482704,0.0005951412,0.0004084705,0.002478535,0.02345457,0.7557322,0.1957965],"study_design_scores_gemma":[0.0001006456,0.0001876906,0.003208217,0.002725405,0.00009200045,0.03281685,0.001794971,0.001557557,0.0009056345,0.1255429,0.8309363,0.0001318215],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0007777165,0.04154255,0.001124831,0.9466738,0.008150019,0.00001330546,0.0000469213,0.00004637522,0.001624546],"genre_scores_gemma":[0.02073841,0.08041783,0.004257699,0.7128708,0.1786267,0.00005468897,0.0001550966,0.00005794221,0.002820818],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.0138017,"threshold_uncertainty_score":0.02982438,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07978604969148483,"score_gpt":0.3284122094414898,"score_spread":0.248626159750005,"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."}}