{"id":"W4306176764","doi":"10.1099/mgen.0.000894","title":"Corrigendum: Coupling next-generation sequencing to dominant positive screens for finding antibiotic cellular targets and resistance mechanisms in Escherichia coli","year":2022,"lang":"en","type":"erratum","venue":"Microbial Genomics","topic":"Antibiotic Resistance in Bacteria","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Escherichia coli; Principal (computer security); Antibiotic resistance; Biology; Microbiology; Antibiotics; Computational biology; Data science; Biotechnology; Computer science; Genetics; Gene; Computer security","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":[0.002530044,0.00336097,0.001990046,0.003111557,0.002977077,0.004153416,0.003610807,0.006108649,0.04150054],"category_scores_gemma":[0.01965118,0.001575417,0.002025654,0.001981836,0.001863594,0.001980827,0.001205493,0.006324158,0.03853123],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00308389,"about_ca_system_score_gemma":0.002546062,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01020995,"about_ca_topic_score_gemma":0.02066566,"domain_scores_codex":[0.9972883,0.0004926848,0.0004432455,0.0004159368,0.001120997,0.0002388777],"domain_scores_gemma":[0.9881126,0.002839326,0.0004667141,0.0006540476,0.00692672,0.001000517],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002622157,0.00001889757,0.00005043631,0.0001350965,0.00001260569,0.0002262105,0.000008863054,0.00005843171,0.0002182439,0.0002883156,0.9934717,0.00548488],"study_design_scores_gemma":[0.0000516827,0.00009387991,0.001683009,0.0002470879,0.0001131525,0.0009860082,0.00007617265,0.0006279984,0.001994175,0.001449725,0.9925981,0.00007912744],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.0001310976,0.001052697,0.0006222926,0.01834174,0.9768281,0.00002688981,0.0002335553,0.0002038385,0.002559741],"genre_scores_gemma":[0.009421983,0.01384605,0.006988844,0.0916872,0.5074277,0.0002774097,0.002411818,0.001309392,0.3666297],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.04150054,"threshold_uncertainty_score":0.1388331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02773192507056364,"score_gpt":0.2383266500174485,"score_spread":0.2105947249468848,"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."}}