{"id":"W2763173272","doi":"10.1128/genomea.01045-17","title":"Metagenomic Sequencing of Bronchoalveolar Lavage Samples from Feedlot Cattle Mortalities Associated with Bovine Respiratory Disease","year":2017,"lang":"en","type":"article","venue":"Genome Announcements","topic":"Microbial infections and disease research","field":"Immunology and Microbiology","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada; Alberta Livestock and Meat Agency; Government of Canada","keywords":"Bovine respiratory disease; Feedlot; Bronchoalveolar lavage; Biology; Metagenomics; Beef cattle; Veterinary medicine; Animal science; Immunology; Internal medicine; Medicine; Gene; Genetics; Lung","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":[0.0003975976,0.0005517575,0.0005215287,0.00116614,0.0006777095,0.0007082948,0.000227713,0.0005055577,0.0005330157],"category_scores_gemma":[0.0004433913,0.0002377808,0.0004441227,0.000901062,0.0002344937,0.0002486482,0.0003819662,0.0004283754,0.0002454729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003691468,"about_ca_system_score_gemma":0.0003101805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002473552,"about_ca_topic_score_gemma":0.00581588,"domain_scores_codex":[0.9995946,0.00004935075,0.00002379708,0.0001242063,0.0001146909,0.00009334694],"domain_scores_gemma":[0.9997455,0.0000541589,0.0000676286,0.00001875684,0.00006767255,0.00004623734],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0005817728,0.00007094128,0.04642085,0.00009790334,0.0001102457,0.0001458412,0.0003599069,0.0002530757,0.9471616,0.00003723491,0.0001814817,0.00457904],"study_design_scores_gemma":[0.00002533876,0.0006467567,0.8889049,0.00007182325,0.0004118073,0.0007885529,0.00131566,0.002307008,0.09963915,0.000147221,0.005706239,0.00003560649],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99131,0.0006184423,0.000847388,0.00008189728,0.00001594257,0.00002889452,0.006657329,0.00002266078,0.0004174058],"genre_scores_gemma":[0.9751892,0.0006733362,0.00338138,0.0001743487,0.00002308664,0.0000721398,0.01907716,0.0000288946,0.001380423],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002473552,"threshold_uncertainty_score":0.004918277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06693025566207234,"score_gpt":0.2893158334397667,"score_spread":0.2223855777776944,"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."}}