{"id":"W3093345697","doi":"10.1101/2020.10.13.337345","title":"Analysis of selection methods to develop novel phage therapy cocktails against antimicrobial resistant clinical isolates of bacteria","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Bacteriophages and microbial interactions","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Medical Research Council; University of Leicester; Directorate for Biological Sciences; Natural Environment Research Council; Science Foundation Ireland; University of Oxford; Biotechnology and Biological Sciences Research Council; Bill and Melinda Gates Foundation; University Hospitals of Leicester NHS Trust; Department of Health and Social Care; King Saud University; Sight Research UK; Wellcome Trust; National Institute for Health and Care Research","keywords":"Phage therapy; Microbiology; Biology; Antimicrobial; Klebsiella; Bacteria; Bacteriophage; Virulence; Escherichia coli; Antibiotic resistance; Biofilm; Enterobacter; Virology; Antibiotics; Gene","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":[0.001156755,0.0006831451,0.0006160931,0.0008712681,0.0002274099,0.0008230856,0.000377702,0.0004869442,0.001607248],"category_scores_gemma":[0.001342022,0.0002930938,0.0005793803,0.0005748804,0.0002081721,0.0004221588,0.0005654392,0.0005701467,0.0006023214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002530709,"about_ca_system_score_gemma":0.0002340106,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002722901,"about_ca_topic_score_gemma":0.0002912951,"domain_scores_codex":[0.9987071,0.0003090875,0.0001279793,0.0002186047,0.0005377684,0.00009951321],"domain_scores_gemma":[0.9991208,0.0003369123,0.000198632,0.00007528464,0.0001946458,0.00007370159],"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":[0.00009822749,0.0001711663,0.0009412282,0.00009567755,0.00001862545,0.000024586,0.00002390343,0.0004365065,0.9892468,0.00005390482,0.00007510241,0.008814213],"study_design_scores_gemma":[0.00001729158,0.002034532,0.005079599,0.00002039818,0.00004936526,0.0001873797,0.00004545378,0.004548979,0.9859726,0.00005126121,0.001977199,0.00001580723],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9466966,0.002585102,0.04710937,0.0002001345,0.00009117794,0.0005592596,0.0006232031,0.0002502886,0.001884754],"genre_scores_gemma":[0.9184139,0.002061545,0.07366621,0.0001488502,0.00002996178,0.0005214186,0.001343637,0.0001018958,0.003712511],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.001607248,"threshold_uncertainty_score":0.006117642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0341519570616193,"score_gpt":0.310114109760697,"score_spread":0.2759621526990776,"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."}}