{"id":"W2041358155","doi":"10.1016/j.gene.2014.01.019","title":"Diagnosis and therapeutic monitoring of inborn errors of creatine metabolism and transport using liquid chromatography–tandem mass spectrometry in urine, plasma and CSF","year":2014,"lang":"en","type":"article","venue":"Gene","topic":"Muscle metabolism and nutrition","field":"Biochemistry, Genetics and Molecular Biology","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"","keywords":"Creatine; Analyte; Urine; Chromatography; Tandem mass spectrometry; Mass spectrometry; Liquid chromatography–mass spectrometry; High-performance liquid chromatography; Chemistry; Creatinine; Biochemistry","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":[0.0001767201,0.0001176259,0.0002595003,0.0001282522,0.00002423954,0.000004302908,0.00004437736,0.00009408879,0.000002600342],"category_scores_gemma":[0.00001391956,0.0001133164,0.00003568087,0.0001397247,0.00008822534,0.000005326553,0.00002222142,0.00004505015,1.879961e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001755712,"about_ca_system_score_gemma":0.000008343259,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006309367,"about_ca_topic_score_gemma":0.00001063027,"domain_scores_codex":[0.9993184,0.00004383045,0.0002165365,0.0002125804,0.00007898539,0.0001297248],"domain_scores_gemma":[0.9996983,0.00001582665,0.0000821158,0.0001262012,0.00002910485,0.00004846582],"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":[0.00007963876,0.00003363704,0.2106239,0.00007825621,0.00003290776,5.337548e-7,0.00004429163,0.000005599997,0.7870375,0.00001612175,3.671482e-7,0.002047228],"study_design_scores_gemma":[0.0007007499,0.0001097001,0.3991231,0.0000289767,0.00004763081,0.00000470419,0.00002767147,0.00003588615,0.5996959,0.00004901633,0.0001036236,0.0000731092],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9843313,0.01512478,0.000331064,0.00001582093,0.00004761105,0.0001076074,0.00001765161,0.000003303947,0.00002093237],"genre_scores_gemma":[0.9855278,0.00930573,0.005023103,0.000009041946,0.000100176,0.000009394229,0.000009902195,0.00001304451,0.000001845901],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1884992,"threshold_uncertainty_score":0.4620907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01205904995817955,"score_gpt":0.2395776139342689,"score_spread":0.2275185639760894,"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."}}