{"id":"W4386964868","doi":"10.1101/2023.09.21.558834","title":"Identification and targeting of microbial putrescine acetylation in bloodstream infections","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Antimicrobial Peptides and Activities","field":"Immunology and Microbiology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Division of Chemistry; National Heart, Lung, and Blood Institute; Canadian Institutes of Health Research; National Science Foundation","keywords":"Microbiology; Biology; Context (archaeology); In vivo; Intracellular; Antimicrobial; Antibiotics; Microbial metabolism; Pathogen; Metabolomics; Bacteria; Bioinformatics; Biochemistry; Biotechnology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003665223,0.000518469,0.0004393319,0.0003985285,0.0001270113,0.0004255585,0.0002356833,0.0004654377,0.00143937],"category_scores_gemma":[0.0002646972,0.0001786941,0.0003013642,0.0002265322,0.000272841,0.000229218,0.0003642446,0.0007371415,0.0006249213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000259395,"about_ca_system_score_gemma":0.0002564366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002801645,"about_ca_topic_score_gemma":0.0004091517,"domain_scores_codex":[0.9998266,0.00003030038,0.00001080206,0.00004106294,0.00006279074,0.00002842275],"domain_scores_gemma":[0.9998564,0.00002341533,0.00004226255,0.00001581547,0.0000254067,0.00003671263],"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":[0.0001703368,0.0000140324,0.0005858034,0.0001072884,0.00001307869,0.00006342286,0.00001284039,0.0001378498,0.9931794,0.0001302563,0.0002048833,0.00538071],"study_design_scores_gemma":[0.00002278177,0.000297704,0.007006601,0.00002087911,0.0000219458,0.0006493963,0.00002245421,0.001407314,0.9835098,0.0003183263,0.006713125,0.000009682603],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9368947,0.02396969,0.03076204,0.001339691,0.0003274955,0.0001122387,0.002188975,0.0005409507,0.003864301],"genre_scores_gemma":[0.957745,0.008277223,0.02720681,0.0004990567,0.0001547473,0.00007492732,0.002243404,0.0001215111,0.003677425],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00143937,"threshold_uncertainty_score":0.004815161,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01138017272855919,"score_gpt":0.2166495493071784,"score_spread":0.2052693765786192,"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."}}