{"id":"W4415813423","doi":"10.3390/antibiotics14111098","title":"Respiratory Bacteria and Antimicrobial Resistance Genes Detected by Long-Read Metagenomic Sequencing Following Feedlot Arrival, Subsequent Treatment Risk and Phenotypic Resistance in Feedlot Calves","year":2025,"lang":"en","type":"article","venue":"Antibiotics","topic":"Microbial infections and disease research","field":"Immunology and Microbiology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Agency of Canada; University of Manitoba; University of Alberta; University of Saskatchewan","funders":"Genome Prairie; Genome Alberta; Alberta Agriculture and Forestry; University of Saskatchewan; University of Alberta; Ministry of Agriculture - Saskatchewan; Genome Canada","keywords":"Feedlot; Metagenomics; Bovine respiratory disease; Antibiotic resistance; Bacteria; Tetracycline; Antimicrobial; Antibiotics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003808872,0.0003494737,0.0005195254,0.0003199914,0.0005381627,0.0001187978,0.0001500967,0.0002852635,0.00003965213],"category_scores_gemma":[0.0001073621,0.0003335871,0.000118564,0.000373591,0.0003623644,0.0001322587,0.0001241026,0.0002850205,0.00001785909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003575733,"about_ca_system_score_gemma":0.0002730255,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009333856,"about_ca_topic_score_gemma":0.005205855,"domain_scores_codex":[0.9977487,0.0004562969,0.0004913632,0.0006715112,0.00004280533,0.0005892712],"domain_scores_gemma":[0.9991388,0.0001948209,0.0001365255,0.0004007041,0.00006369551,0.00006541861],"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":[0.0003252456,0.0001367604,0.04167459,0.0001427421,0.0003633513,0.0000217129,0.0001772205,0.000006722554,0.9549778,0.0002082785,0.000707271,0.001258353],"study_design_scores_gemma":[0.004180918,0.0001719679,0.1835738,0.0005126212,0.0004351408,0.00001106482,0.0002197677,0.000004688059,0.8003007,0.0001705711,0.009777954,0.0006408448],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9571307,0.04123442,0.0002090136,0.0001037029,0.0003296605,0.000481311,0.0002279829,0.00006715566,0.000216027],"genre_scores_gemma":[0.9929234,0.003936179,0.0003787146,0.00009233677,0.00002032102,0.000003457553,0.00007548914,0.00003069293,0.002539441],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1546771,"threshold_uncertainty_score":0.9999116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01681284303933952,"score_gpt":0.267892236848755,"score_spread":0.2510793938094155,"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."}}