{"id":"W4312032573","doi":"10.1021/acs.analchem.2c01610","title":"Cov<sup>2</sup>MS: An Automated and Quantitative Matrix-Independent Assay for Mass Spectrometric Measurement of SARS-CoV-2 Nucleocapsid Protein","year":2022,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"SARS-CoV-2 detection and testing","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"H2020 Research Infrastructures; Bijzonder Onderzoeksfonds UGent; Medical Research Council; Natural Sciences and Engineering Research Council of Canada; Fonds Wetenschappelijk Onderzoek","keywords":"Chemistry; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Coronavirus disease 2019 (COVID-19); Mass spectrometry; Matrix (chemical analysis); Chromatography; Virology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001223332,0.0002523231,0.0005366344,0.0002046071,0.0001657351,0.00003581716,0.0001537656,0.0001233565,0.0001085023],"category_scores_gemma":[0.001629249,0.0002509212,0.0001720652,0.0008682183,0.00011526,0.00007090987,0.00008863497,0.0004251522,0.000006092047],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003869896,"about_ca_system_score_gemma":0.000204481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006839353,"about_ca_topic_score_gemma":0.000002171008,"domain_scores_codex":[0.9974747,0.00008655947,0.0005488782,0.0005357675,0.0009644809,0.0003895897],"domain_scores_gemma":[0.9988138,0.0001787338,0.0002077993,0.0003466234,0.0003480234,0.0001050221],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003508472,0.0003114119,0.0006314042,0.0004175872,0.0002429396,0.00004815565,0.00008657619,0.00002065158,0.997252,0.000151933,0.000331825,0.0001547096],"study_design_scores_gemma":[0.001841017,0.000633849,0.000130341,0.00005993031,0.0002334612,0.00009912757,0.0006347835,0.1797097,0.8155422,0.0001983107,0.0007046303,0.0002126561],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942451,0.0002096512,0.001684111,0.0002113194,0.00002452153,0.0006303373,0.00004686675,0.0002764796,0.002671654],"genre_scores_gemma":[0.995441,0.000001486092,0.004008189,0.0002117111,0.00006775406,0.00009765211,0.00002465717,0.00004468646,0.0001028453],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1817097,"threshold_uncertainty_score":0.9999943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06850463563493725,"score_gpt":0.3489571652610759,"score_spread":0.2804525296261386,"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."}}