{"id":"W4410122355","doi":"10.1186/s13073-025-01480-2","title":"Simultaneous detection of pathogens and antimicrobial resistance genes with the open source, cloud-based, CZ ID platform","year":2025,"lang":"en","type":"article","venue":"Genome Medicine","topic":"Antibiotic Resistance in Bacteria","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"National Heart, Lung, and Blood Institute; Canadian Institutes of Health Research; National Institutes of Health; Chan Zuckerberg Initiative; National Institute of Allergy and Infectious Diseases; McMaster University","keywords":"Resistome; Metagenomics; Antibiotic resistance; Workflow; Computational biology; Biodefense; Genome; Bioinformatics; Biology; Gene; Computer science; Genetics; Microbiology; Antibiotics; Database; Mobile genetic elements","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002890771,0.001283775,0.0007242364,0.001991329,0.0007448881,0.00190753,0.002150203,0.0008264757,0.003187769],"category_scores_gemma":[0.004785617,0.0006471956,0.001250283,0.00144852,0.0007146421,0.001602785,0.003347519,0.001273937,0.002124471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001190591,"about_ca_system_score_gemma":0.002463859,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006257006,"about_ca_topic_score_gemma":0.008514205,"domain_scores_codex":[0.997475,0.0002379433,0.0001453539,0.001100368,0.0007959205,0.0002454294],"domain_scores_gemma":[0.9971962,0.0005942355,0.0004703454,0.0005823839,0.0007503299,0.0004064307],"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":[0.00678835,0.001013833,0.150301,0.001596257,0.00128856,0.001762424,0.001619865,0.04901323,0.4171435,0.01298343,0.07688001,0.2796096],"study_design_scores_gemma":[0.0006975534,0.0006225655,0.05924735,0.0002543138,0.0003445373,0.0007978734,0.0005025007,0.5770887,0.2664649,0.01947902,0.07397923,0.0005214133],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2052503,0.00114823,0.6374256,0.00138614,0.0005078654,0.001131397,0.03921308,0.1035523,0.01038508],"genre_scores_gemma":[0.3605861,0.0003927518,0.5960692,0.001476519,0.0001472454,0.0007673627,0.0340138,0.003810718,0.002736365],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006257006,"threshold_uncertainty_score":0.015288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006083127524444403,"score_gpt":0.2301543821244158,"score_spread":0.2240712545999714,"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."}}