{"id":"W4388962256","doi":"10.1016/j.xpro.2023.102736","title":"Protocol for mapping the metabolome and lipidome of medulloblastoma cells using liquid chromatography-mass spectrometry","year":2023,"lang":"en","type":"article","venue":"STAR Protocols","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Cancer Society Research Institute; Canadian Institutes of Health Research","keywords":"Lipidome; Metabolome; Metabolomics; Lipidomics; Liquid chromatography–mass spectrometry; Medulloblastoma; Mass spectrometry; Metabolite; Chromatography; Chemistry; Computational biology; Biology; Biochemistry; Cancer research","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":[],"consensus_categories":[],"category_scores_codex":[0.0008119567,0.0002699508,0.0004262675,0.0002511609,0.0002232176,0.00003977516,0.0003034268,0.0001249408,0.00001910379],"category_scores_gemma":[0.0001174083,0.0001944026,0.0002100164,0.0007403544,0.000222422,0.000008142589,0.0002484318,0.0001021999,0.000002314817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001059769,"about_ca_system_score_gemma":0.00007951348,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000757822,"about_ca_topic_score_gemma":0.000004014856,"domain_scores_codex":[0.9983008,0.00009437881,0.0004466349,0.0004640632,0.0002173273,0.0004768157],"domain_scores_gemma":[0.9989685,0.00005757255,0.0002894529,0.0004703484,0.0001379442,0.00007617498],"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":[0.0003758562,0.00004222272,0.0002701817,0.0003901898,0.0002067204,7.86216e-7,0.00005480041,0.00001054732,0.9971895,0.0004889641,0.0008423768,0.0001278978],"study_design_scores_gemma":[0.001711707,0.001237831,0.0007771144,0.00007162624,0.00002924253,0.000004928683,0.0002274616,0.0001485815,0.8519499,0.0006366119,0.1429371,0.0002678858],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"protocol","genre_gemma":"protocol","genre_scores_codex":[0.1995623,0.00007218318,0.003728861,0.0001535117,0.00008785191,0.7959729,0.000134247,0.00005192586,0.0002361614],"genre_scores_gemma":[0.01857699,0.00001819549,0.01417735,0.00006013981,0.0003155671,0.9666455,0.0000124094,0.00005163992,0.0001421607],"genre_candidate":"protocol","genre_consensus":"protocol","teacher_disagreement_score":0.1809853,"threshold_uncertainty_score":0.7927507,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05127737209146427,"score_gpt":0.329555598263666,"score_spread":0.2782782261722018,"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."}}