{"id":"W2947293772","doi":"10.3390/antibiotics8020065","title":"Development of a High Throughput Screen for the Identification of Inhibitors of Peptidoglycan O-Acetyltransferases, New Potential Antibacterial Targets","year":2019,"lang":"en","type":"article","venue":"Antibiotics","topic":"Glycosylation and Glycoproteins Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Canadian Glycomics Network; McMaster University; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Scheme for Promotion of Academic and Research Collaboration; University of Toronto","keywords":"Peptidoglycan; Microbiology; Neisseria gonorrhoeae; Sydnone; Lytic cycle; Biochemistry; Escherichia coli; High-throughput screening; Enzyme; Biology; Ribitol; Chemistry; Virology","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":[0.0002689116,0.00009993545,0.0001758887,0.0000452885,0.00004331732,0.0000097703,0.0002073168,0.0001081962,0.00003212077],"category_scores_gemma":[0.00005482887,0.00008010954,0.00009891955,0.00009787457,0.00008608836,0.000005981402,0.00006064631,0.00004350414,0.000003099138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006207122,"about_ca_system_score_gemma":0.0002497413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001330032,"about_ca_topic_score_gemma":0.00005455587,"domain_scores_codex":[0.998902,0.00002528697,0.0005065519,0.0001916806,0.000223742,0.000150781],"domain_scores_gemma":[0.9991951,0.00001595859,0.0002136873,0.0003124795,0.0002282778,0.00003449564],"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":[0.000279923,0.00007526016,0.001009149,0.0001097164,0.00008760115,8.660368e-8,0.0001072973,0.000111954,0.9945484,0.000206425,0.0002440399,0.003220162],"study_design_scores_gemma":[0.0008748776,0.0002159249,0.009974726,0.00002651173,0.00002074656,9.394277e-7,0.00008798188,0.0001223695,0.9849505,0.0000180609,0.003623003,0.00008437952],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9656289,0.0001116134,0.03320715,0.00009219367,0.0002268333,0.0006101975,0.00009201611,0.000002968279,0.00002812663],"genre_scores_gemma":[0.9924682,0.00009144915,0.006693683,0.00001067856,0.0001194721,5.543244e-7,0.0002626316,0.00001520126,0.0003381296],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0268393,"threshold_uncertainty_score":0.3266772,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01120206476459271,"score_gpt":0.2614979673819579,"score_spread":0.2502959026173651,"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."}}