{"id":"W4387976851","doi":"10.1101/2023.10.25.563906","title":"Unpredictability of the fitness effects of antimicrobial resistance mutations across environments in <i>Escherichia coli</i>","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; McGill University; University of Ottawa","funders":"","keywords":"Biology; Context (archaeology); Antibiotic resistance; Mutation Accumulation; Mutation; Genetics; Genotype; Genetic variation; Genetic Fitness; Resistance (ecology); Mutation rate; Evolutionary biology; Antibiotics; Ecology; Biological evolution; 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":[0.0007030877,0.0003757281,0.0003160019,0.0004148283,0.0003174921,0.0005811617,0.0004745635,0.0005716733,0.0006238724],"category_scores_gemma":[0.004207918,0.0001779417,0.0004426134,0.0003343047,0.0004677474,0.0005010983,0.0003901829,0.0005717477,0.0001019792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001223174,"about_ca_system_score_gemma":0.000439001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008307721,"about_ca_topic_score_gemma":0.006064266,"domain_scores_codex":[0.9996158,0.0001394085,0.00002311209,0.00009358121,0.00005488925,0.00007317084],"domain_scores_gemma":[0.997846,0.001326478,0.0003867334,0.0001497528,0.0001879645,0.000103126],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001538163,0.0002262973,0.0991966,0.00006392573,0.0001206834,0.0002630377,0.00007799293,0.8682109,0.02473443,0.001562791,0.0004356191,0.004953792],"study_design_scores_gemma":[0.0000112802,0.0001988795,0.06123065,0.000009556889,0.00003739968,0.0001132573,0.000100152,0.9297183,0.007375916,0.0009601801,0.0002053,0.00003909653],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972563,0.0000297252,0.002221643,0.0000505406,0.000003903451,0.000004761323,0.00007425425,0.00002702933,0.000331828],"genre_scores_gemma":[0.9991248,0.00001792482,0.0006761853,0.00001072177,8.422191e-7,0.000005613726,0.00007380543,0.000005882562,0.00008419565],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008307721,"threshold_uncertainty_score":0.01651871,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006355049807660609,"score_gpt":0.2194120009927958,"score_spread":0.2130569511851352,"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."}}