{"id":"W4399715349","doi":"10.1016/j.cell.2024.05.035","title":"A metabolomics pipeline highlights microbial metabolism in bloodstream infections","year":2024,"lang":"en","type":"article","venue":"Cell","topic":"Antimicrobial Peptides and Activities","field":"Immunology and Microbiology","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; National Heart, Lung, and Blood Institute; Canadian Institutes of Health Research; National Institute of General Medical Sciences; National Sleep Foundation; Howard Hughes Medical Institute; Division of Chemistry; Canadian HIV Trials Network, Canadian Institutes of Health Research; National Science Foundation","keywords":"Biology; Metabolomics; Context (archaeology); Microbial metabolism; Microbiology; Metabolism; Antibiotic resistance; Bacteria; Antibiotics; Computational biology; Bioinformatics; Biochemistry; Genetics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001216112,0.0002026445,0.0003021831,0.0002470342,0.000102025,0.00005483908,0.0001334359,0.0002249887,0.0007161332],"category_scores_gemma":[0.00001122236,0.0001749445,0.0001551382,0.000256848,0.0001462618,0.0001596164,0.00007517548,0.0003857948,0.001462999],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002732707,"about_ca_system_score_gemma":0.00007685805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004639379,"about_ca_topic_score_gemma":0.0002043479,"domain_scores_codex":[0.9989506,0.00007927608,0.0002713699,0.0003284816,0.00001682126,0.0003534579],"domain_scores_gemma":[0.9996474,0.00009077924,0.00003807094,0.0001814968,0.00002353525,0.00001867674],"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":[0.000017126,0.0002654513,0.00005089989,0.00004098949,0.00005982986,0.00002119359,0.0003735726,0.00002006275,0.9638713,0.002577707,0.03181862,0.0008832654],"study_design_scores_gemma":[0.0004991696,0.00002239098,0.0001295244,0.00003187492,0.00007943948,0.00005188259,0.00008698283,0.00001261547,0.5404426,0.0001715702,0.4582978,0.0001741271],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9690261,0.0166911,0.0004227405,0.0006932876,0.003740744,0.0002366528,0.0001502478,0.000278254,0.008760877],"genre_scores_gemma":[0.9734864,0.000802342,0.0001590858,0.0001561727,0.0001719191,0.00001222585,0.0001163034,0.00002858334,0.02506692],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4264792,"threshold_uncertainty_score":0.9993145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007316151901708792,"score_gpt":0.214393100170915,"score_spread":0.2070769482692062,"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."}}