{"id":"W3139421153","doi":"10.1016/j.jmsacl.2021.03.001","title":"Analysis of 2-methylcitric acid, methylmalonic acid, and total homocysteine in dried blood spots by LC-MS/MS for application in the newborn screening laboratory: A dual derivatization approach","year":2021,"lang":"en","type":"article","venue":"Journal of Mass Spectrometry and Advances in the Clinical Lab","topic":"Metabolism and Genetic Disorders","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Children's Hospital; University of British Columbia","funders":"United Arab Emirates University","keywords":"Methylmalonic acid; Dried blood spot; Analyte; Derivatization; Newborn screening; Chemistry; Chromatography; Methylmalonic acidemia; Tandem mass spectrometry; Selected reaction monitoring; Protein precipitation; Homocysteine; Liquid chromatography–mass spectrometry; Methionine; Retention time; High-performance liquid chromatography; Mass spectrometry; Medicine; Amino acid; Biochemistry; Internal medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.00256219,0.0001213869,0.0004550882,0.0002037289,0.00003530054,0.00002704239,0.0001957324,0.0001217624,0.000002637701],"category_scores_gemma":[0.0008933262,0.00008305393,0.000117728,0.001591034,0.0001038575,0.00002434274,0.00004185369,0.0002348643,2.702225e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003005534,"about_ca_system_score_gemma":0.00004992375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003327398,"about_ca_topic_score_gemma":0.00004288179,"domain_scores_codex":[0.9981486,0.0005011003,0.0007362406,0.0002570613,0.0001951162,0.0001618356],"domain_scores_gemma":[0.998902,0.0003197396,0.0004271721,0.0002162972,0.00009678378,0.00003800218],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001607568,0.00236358,0.310615,0.0002683789,0.001211892,0.00002521775,0.0006706606,0.003497878,0.5785973,0.001851704,0.00008388649,0.09920695],"study_design_scores_gemma":[0.02448009,0.003393646,0.7610345,0.0001563184,0.003292197,0.000151911,0.00956696,0.004493928,0.1639449,0.007140002,0.02127709,0.001068489],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9043402,0.03870232,0.05628984,0.0003470199,0.00003319369,0.0001868886,0.00003388636,8.181095e-7,0.00006580405],"genre_scores_gemma":[0.9674514,0.009000343,0.02318937,0.0001677556,0.0001018018,0.00001566297,0.00005914786,0.000007252831,0.00000724943],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4504195,"threshold_uncertainty_score":0.3386841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01025095447071845,"score_gpt":0.3011703301282148,"score_spread":0.2909193756574964,"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."}}