{"id":"W4400344918","doi":"10.21203/rs.3.rs-3192981/v2","title":"Changes in neuroinflammatory biomarkers correlate with disease severity and neuroimaging alterations in patients with COVID-19 neurological complications.","year":2024,"lang":"en","type":"preprint","venue":"Research Square","topic":"Long-Term Effects of COVID-19","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Neuroimaging; Coronavirus disease 2019 (COVID-19); Neuroinflammation; Medicine; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Disease; 2019-20 coronavirus outbreak; Intensive care medicine; Severity of illness; Neuroscience; Internal medicine; Pathology; Psychology; Psychiatry; Infectious disease (medical specialty)","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0008018917,0.0004358933,0.0006750565,0.0004840537,0.0005656422,0.0009844289,0.0002879172,0.0005321484,0.002707084],"category_scores_gemma":[0.004391857,0.0001764659,0.000469877,0.0008047854,0.0003504013,0.0006064603,0.0007310932,0.00125046,0.0004492257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003787012,"about_ca_system_score_gemma":0.0006056767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001983288,"about_ca_topic_score_gemma":0.002039911,"domain_scores_codex":[0.9995539,0.000105463,0.00004857194,0.00009334144,0.0000708181,0.0001278757],"domain_scores_gemma":[0.9974846,0.0003388744,0.001234809,0.0002019416,0.0002500671,0.000489771],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.007464045,0.0005283659,0.958137,0.0001744834,0.0007512505,0.001580598,0.0002234226,0.00014908,0.004699823,0.0001829387,0.001845141,0.02426395],"study_design_scores_gemma":[0.0000345324,0.0004658684,0.9970343,0.00003602639,0.0001290428,0.0009468112,0.0001025425,0.0000775943,0.0003486263,0.000244721,0.0005684714,0.00001144774],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9912258,0.004171001,0.0003242698,0.0004305838,0.00008347417,0.00003268469,0.001460291,0.0000190713,0.002252885],"genre_scores_gemma":[0.9950284,0.001362503,0.0003182251,0.0001245737,0.0001310541,0.00003537402,0.002306132,0.000008323383,0.0006853546],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002707084,"threshold_uncertainty_score":0.009056151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03646684547826307,"score_gpt":0.3655392742461597,"score_spread":0.3290724287678966,"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."}}