{"id":"W3125529955","doi":"10.1016/j.clinbiochem.2021.01.003","title":"Anti-SARS-CoV-2 IgM improves clinical sensitivity early in disease course","year":2021,"lang":"en","type":"article","venue":"Clinical Biochemistry","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"University Health Network; University of Toronto","funders":"","keywords":"Medicine; Serology; Seroconversion; Concordance; Antibody; Immunoglobulin M; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Immunology; Coronavirus disease 2019 (COVID-19); Immunoglobulin G; Virology; Disease; Internal medicine; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002377057,0.000318174,0.0009946951,0.00004459648,0.00006498465,0.00006734957,0.0002245041,0.000657237,0.00001347752],"category_scores_gemma":[0.009242292,0.0003003451,0.0007272956,0.0004503269,0.0008505034,0.00007677881,0.0003712257,0.001660441,0.0002431427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007631024,"about_ca_system_score_gemma":0.002275034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004823238,"about_ca_topic_score_gemma":0.00001882145,"domain_scores_codex":[0.9957211,0.0003812698,0.001343268,0.001286294,0.0005922978,0.0006757866],"domain_scores_gemma":[0.9962411,0.001544581,0.0001734871,0.00137079,0.0003734952,0.0002965455],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006044942,0.002189611,0.5937279,0.0001905563,0.00009185095,0.004559552,0.00001045191,1.6735e-8,0.3913017,0.000007865372,0.001467034,0.005849031],"study_design_scores_gemma":[0.003308856,0.0001611925,0.4595694,0.0002321898,0.0001337082,0.00004880941,0.00004406772,0.0002482771,0.526659,0.0001102721,0.009171191,0.0003130329],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9947217,0.0008976867,0.00001863506,0.002395383,0.0004401082,0.000262434,0.00004968194,0.0001039714,0.001110464],"genre_scores_gemma":[0.9603675,0.00005982273,0.0001721036,0.03793091,0.001235589,0.00001729476,0.00003429347,0.0000434459,0.0001390518],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1353573,"threshold_uncertainty_score":0.9999449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08385824418212703,"score_gpt":0.4532032848686931,"score_spread":0.369345040686566,"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."}}