{"id":"W4384661026","doi":"10.20944/preprints202307.1116.v1","title":"Impact of Environmental Sub-Inhibitory Concentrations of Antibiotics, Heavy Metals, and Biocides on the Emergence of Tolerance and Effects on the Mutant Selection Window in E. coli","year":2023,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Medical Research Council; South African Medical Research Council; National Research Foundation","keywords":"Biocide; Microbiology; Biology; Mutant; Minimum inhibitory concentration; Ampicillin; Antimicrobial; Population; Antibiotics; Antibiotic resistance; Drug tolerance; Persistence (discontinuity); Bacteria; Chemistry; Genetics; Gene; Pharmacology; Medicine","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":[0.0001111503,0.0002613418,0.0003554976,0.0001806856,0.0001198142,0.0004970285,0.0001760038,0.0003131749,0.001155478],"category_scores_gemma":[0.0003324572,0.0001254704,0.0001857817,0.0001800457,0.0001681312,0.0001801863,0.000308606,0.0003964631,0.0001961393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002353446,"about_ca_system_score_gemma":0.0002325158,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001591715,"about_ca_topic_score_gemma":0.001684736,"domain_scores_codex":[0.99977,0.0000407455,0.00002428625,0.00004687543,0.00006021818,0.00005791871],"domain_scores_gemma":[0.9998133,0.00005063396,0.00004116504,0.00001987622,0.00003252447,0.00004263969],"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":[0.0002283114,0.00006431418,0.002395883,0.0000550785,0.000011717,0.00006701126,0.00002793296,0.0003884509,0.9940451,0.00006746074,0.00008395721,0.002564591],"study_design_scores_gemma":[0.000008269597,0.0005958382,0.04405382,0.00001337702,0.00002629732,0.0001575359,0.0001421883,0.002478712,0.9511777,0.000125809,0.00120173,0.00001876181],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968724,0.0005136668,0.0008141344,0.00009369473,0.00002375387,0.00001018424,0.0004828394,0.00002878855,0.001160555],"genre_scores_gemma":[0.9974155,0.0002838241,0.0008197574,0.00005781164,0.000004021022,0.00001360083,0.0003371442,0.00001659587,0.001051649],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001591715,"threshold_uncertainty_score":0.003865421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03276176409934763,"score_gpt":0.2975790798909386,"score_spread":0.264817315791591,"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."}}