{"id":"W4386588129","doi":"10.1016/j.mimet.2023.106815","title":"Evaluation of metagenomic assembly methods for the detection and characterization of antimicrobial resistance determinants and associated mobilizable elements","year":2023,"lang":"en","type":"article","venue":"Journal of Microbiological Methods","topic":"Antibiotic Resistance in Bacteria","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Agency of Canada; University of Lethbridge; Government of Canada; Agriculture and Agri-Food Canada","funders":"Government of Canada; Government of Alberta","keywords":"Metagenomics; Resistome; Mobile genetic elements; Antibiotic resistance; Biology; Context (archaeology); Horizontal gene transfer; Computational biology; Biotechnology; Workflow; Expediting; Genetics; Genome; Gene; Computer science; Engineering; Bacteria; Database","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":[0.01166572,0.0001150546,0.0003509159,0.0000673117,0.00007191746,0.00001467072,0.0001400095,0.0001749676,0.000003185998],"category_scores_gemma":[0.002259153,0.00007660616,0.0001035246,0.0001419444,0.0001650676,0.00001072327,0.0000741957,0.0000731102,6.720649e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000242924,"about_ca_system_score_gemma":0.0000563307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001013091,"about_ca_topic_score_gemma":0.000005593018,"domain_scores_codex":[0.9974263,0.001508035,0.0006540093,0.000180908,0.00008533715,0.0001453688],"domain_scores_gemma":[0.9978738,0.0003548295,0.001042972,0.0001314297,0.0005704233,0.00002653918],"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":[0.0002412426,0.00002965211,0.001380071,0.00003808873,0.0001498487,1.343166e-7,0.00002148091,0.00000602512,0.9508967,0.000002415291,0.00001327418,0.04722107],"study_design_scores_gemma":[0.0007069046,0.0002941056,0.08120148,0.00004957224,0.0002955912,0.00001132238,0.00003786821,0.0005426962,0.9158772,0.0001184519,0.0007876024,0.0000772678],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8872381,0.0007192233,0.1114588,0.00002504835,0.0002000573,0.0003197536,0.00003328614,0.000002318328,0.000003402881],"genre_scores_gemma":[0.8888124,0.001533776,0.1094989,0.00001891184,0.00004721203,0.000005728682,0.00001615593,0.00001159467,0.00005535608],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07982141,"threshold_uncertainty_score":0.4043129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05526258754300114,"score_gpt":0.4023958996271895,"score_spread":0.3471333120841884,"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."}}