{"id":"W4313907465","doi":"10.1177/03009858221146092","title":"Bronchopneumonia with interstitial pneumonia in beef feedlot cattle: Characterization and laboratory investigation","year":2023,"lang":"en","type":"article","venue":"Veterinary Pathology","topic":"Microbial infections and disease research","field":"Immunology and Microbiology","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; Alberta Health Services; University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Agri-Food Innovation Alliance; Ministry of Agriculture, Food and Rural Affairs; Beef Farmers of Ontario; Ontario Ministry of Agriculture, Food and Rural Affairs; Beef Cattle Research Council","keywords":"Pathology; Lung; Pneumonia; Medicine; Diffuse alveolar damage; Histopathology; Interstitial lung disease; Immunology; Internal medicine","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":[0.000983485,0.0005077184,0.0004007799,0.001481663,0.0005504744,0.0005829426,0.0002579481,0.0005503044,0.0003181606],"category_scores_gemma":[0.001223705,0.0003305795,0.0002010436,0.0007721294,0.0007109508,0.0004279257,0.000283482,0.0002991334,0.0001054997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005541988,"about_ca_system_score_gemma":0.0002709799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004895454,"about_ca_topic_score_gemma":0.004920168,"domain_scores_codex":[0.9994419,0.000119928,0.00006192492,0.00008454354,0.0001406992,0.000150923],"domain_scores_gemma":[0.9993944,0.0001100317,0.0002002147,0.00002554705,0.0001091928,0.0001604757],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003613341,0.0001233701,0.9732353,0.00004829727,0.00002899859,0.002658797,0.0003257376,0.00006301994,0.01940335,0.00001833779,0.00004049634,0.003692918],"study_design_scores_gemma":[0.00001058976,0.0008129299,0.9891112,0.00001272276,0.00003119847,0.007570279,0.0005852199,0.0003047266,0.001353755,0.00001297808,0.0001893284,0.000004951704],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994967,0.0002132056,0.0001003985,0.000007107875,0.000002834221,0.000006993008,0.00002663305,0.000002173418,0.0001438764],"genre_scores_gemma":[0.9994809,0.0001272534,0.0002164277,0.00001889844,0.000009040347,0.000005070938,0.0001003019,6.989614e-7,0.00004141016],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004895454,"threshold_uncertainty_score":0.009733915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02040490748746595,"score_gpt":0.2611704624979313,"score_spread":0.2407655550104653,"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."}}