{"id":"W4413909648","doi":"10.1021/jasms.5c00133","title":"Characterization of <i>Micrococcus luteus</i> Lipidome Containing Novel Lipid Families by Multiple Stage Linear Ion-Trap with High Resolution Mass Spectrometry","year":2025,"lang":"en","type":"article","venue":"Journal of the American Society for Mass Spectrometry","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"IONICS Mass Spectrometry (Canada)","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; National Heart, Lung, and Blood Institute","keywords":"Lipidome; Chemistry; Mass spectrometry; Micrococcus luteus; Chromatography; Ion trap; Resolution (logic); Lipidomics; Analytical Chemistry (journal); Biochemistry; Escherichia coli","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":[0.0001333125,0.0005346154,0.0002000003,0.0007435045,0.0001922101,0.0003186648,0.0001561334,0.000286214,0.0003746865],"category_scores_gemma":[0.0002423733,0.0001095664,0.0002686275,0.0003108513,0.0002016405,0.0002865966,0.0003273811,0.0002346595,0.0002756923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001791463,"about_ca_system_score_gemma":0.0002039968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001233534,"about_ca_topic_score_gemma":0.001255398,"domain_scores_codex":[0.9998622,0.00001550537,0.00001051809,0.0000465277,0.00003899481,0.00002625921],"domain_scores_gemma":[0.9998782,0.00002065219,0.00003770742,0.000009006319,0.00003285702,0.00002162511],"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":[0.00003668786,0.000003923745,0.0008796567,0.00002327818,0.000003854691,0.00006960824,0.00001450445,0.00001457375,0.9977114,0.00001633505,0.00002092948,0.001205289],"study_design_scores_gemma":[0.000008777341,0.000168251,0.04237905,0.00001706116,0.00003395159,0.001067965,0.0001278838,0.001626503,0.9501606,0.0001030683,0.004285472,0.00002145646],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.987358,0.001996838,0.007497027,0.0001588732,0.0000293591,0.00005101538,0.00151509,0.0001650471,0.001228838],"genre_scores_gemma":[0.9709041,0.001528244,0.02168104,0.0002908616,0.00003877296,0.00007257829,0.003496304,0.0000961463,0.001892042],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001233534,"threshold_uncertainty_score":0.002452672,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007902953354182837,"score_gpt":0.2440410396418646,"score_spread":0.2361380862876818,"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."}}