{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007012903,0.00104613,0.000928494,0.001686856,0.0004946037,0.0007231309,0.0005320723,0.001421727,0.0003945677],"category_scores_gemma":[0.002709934,0.0002955652,0.000390898,0.00063481,0.0006489222,0.0005155816,0.0002195218,0.0009830124,0.0001726902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005934456,"about_ca_system_score_gemma":0.0008092626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001290256,"about_ca_topic_score_gemma":0.001294003,"domain_scores_codex":[0.9994133,0.0001573907,0.00008455466,0.0001107339,0.0001931937,0.00004076963],"domain_scores_gemma":[0.9989733,0.0004438375,0.0002136981,0.00003908477,0.0001714039,0.0001588585],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00871473,0.0008763296,0.6828942,0.0004098057,0.0003460973,0.01571754,0.0003592641,0.001934797,0.1697414,0.0005408232,0.002355495,0.1161094],"study_design_scores_gemma":[0.0004067401,0.004960554,0.6595302,0.0003740828,0.0007121814,0.04856563,0.0009951596,0.01868506,0.2563396,0.002068785,0.00724757,0.0001144106],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9740969,0.01375058,0.006835643,0.00108973,0.0001871139,0.00007032594,0.000455344,0.0002639194,0.00325052],"genre_scores_gemma":[0.9935145,0.001402693,0.003926365,0.0003855244,0.00008624832,0.00003150937,0.0001992977,0.00002948188,0.0004244077],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001686856,"threshold_uncertainty_score":0.00430572,"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."}}