{"id":"W1978600425","doi":"10.1016/j.jchromb.2012.10.038","title":"Validation of an LC–MS/MS method for the quantification of choline-related compounds and phospholipids in foods and tissues","year":2012,"lang":"en","type":"article","venue":"Journal of Chromatography B","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":83,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"National Academy of Sciences; Alberta Livestock and Meat Agency; University of Alberta","keywords":"Chemistry; Chromatography; Hydrophilic interaction chromatography; Analyte; Electrospray; Sample preparation; Mass spectrometry; Tandem mass spectrometry; Liquid chromatography–mass spectrometry; Choline; Phospholipid; Electrospray ionization; Extraction (chemistry); Solid phase extraction; Detection limit; Methanol; Selected reaction monitoring; High-performance liquid chromatography; Membrane; Biochemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00385212,0.001504908,0.0006515433,0.001876747,0.001451788,0.0008917969,0.001246067,0.002550089,0.001129539],"category_scores_gemma":[0.004079835,0.0007815031,0.0007558445,0.0006419834,0.001344557,0.0006903908,0.001235166,0.001242398,0.001433951],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009754778,"about_ca_system_score_gemma":0.002796686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003583129,"about_ca_topic_score_gemma":0.005691743,"domain_scores_codex":[0.9965284,0.0005885135,0.0002950122,0.0008470336,0.001577973,0.000163037],"domain_scores_gemma":[0.9971168,0.0005785921,0.0002499885,0.0003112976,0.001527975,0.0002152965],"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":[0.0003036765,0.0001260939,0.001479325,0.0001036592,0.00008829294,0.00007028982,0.00006222702,0.0001521315,0.990465,0.0001153694,0.0001191253,0.006914764],"study_design_scores_gemma":[0.0001122897,0.0009928495,0.009592708,0.00007759914,0.0002312821,0.00108278,0.00006743627,0.003392912,0.9802561,0.0002410764,0.003897258,0.00005580288],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6293519,0.008455821,0.3486871,0.001352411,0.0009531759,0.002084121,0.003159901,0.001788936,0.004166648],"genre_scores_gemma":[0.6971083,0.003827472,0.2811642,0.002614256,0.0002013551,0.002757186,0.004444334,0.0003162216,0.007566569],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.00385212,"threshold_uncertainty_score":0.02037215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01625231933643176,"score_gpt":0.3086427807878952,"score_spread":0.2923904614514635,"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."}}