{"id":"W1966735054","doi":"10.1007/s00216-014-7797-5","title":"Comprehensive and simultaneous coverage of lipid and polar metabolites for endogenous cellular metabolomics using HILIC-TOF-MS","year":2014,"lang":"en","type":"article","venue":"Analytical and Bioanalytical Chemistry","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":70,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; McMaster University","keywords":"Hydrophilic interaction chromatography; Metabolome; Metabolomics; Chemistry; Chromatography; Mass spectrometry; Polar; Sample preparation; Extraction (chemistry); Time-of-flight mass spectrometry; High-performance liquid chromatography","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":[0.0002084072,0.0003135926,0.0007027753,0.00004384979,0.0001291286,0.00004398303,0.0001142091,0.0002295394,0.00001452947],"category_scores_gemma":[0.0005324394,0.0002621516,0.0001586327,0.0001154348,0.0005792275,0.000006379402,0.0002472151,0.0001284667,2.880206e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007362089,"about_ca_system_score_gemma":0.00002860935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002605477,"about_ca_topic_score_gemma":0.000001809728,"domain_scores_codex":[0.9984345,0.00002950518,0.0004030992,0.0005998507,0.0001475506,0.0003854507],"domain_scores_gemma":[0.9989352,0.0002495644,0.0001162463,0.000262704,0.0001747798,0.0002614742],"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":[0.0001461822,0.00008517299,0.001491651,0.0002965744,0.000498952,0.000003305408,0.00001132927,0.00001100315,0.9937209,0.002208169,0.00002395437,0.001502789],"study_design_scores_gemma":[0.001979049,0.0004308961,0.0004104927,0.00002350457,0.001393333,0.0001168552,0.0001307747,0.04264664,0.8839857,0.00159166,0.06654881,0.0007422849],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.987107,0.008344942,0.00308948,0.0001596363,0.00003484734,0.0001691027,0.0001898454,0.000009037233,0.0008961427],"genre_scores_gemma":[0.9947504,0.002784926,0.001716933,0.0001769901,0.0002830074,0.000004059786,0.00005846146,0.0000233371,0.0002018457],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1097352,"threshold_uncertainty_score":0.9999831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01928920142224802,"score_gpt":0.2440554778468323,"score_spread":0.2247662764245843,"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."}}