{"id":"W2280176900","doi":"10.1016/j.prevetmed.2016.01.027","title":"Bayesian evaluation of clinical diagnostic test characteristics of visual observations and remote monitoring to diagnose bovine respiratory disease in beef calves","year":2016,"lang":"en","type":"article","venue":"Preventive Veterinary Medicine","topic":"Microbial infections and disease research","field":"Immunology and Microbiology","cited_by":33,"is_retracted":false,"has_abstract":false,"ca_institutions":"Alberta Health Services","funders":"","keywords":"Bovine respiratory disease; Gold standard (test); Medicine; Credible interval; Positive predicative value; Diagnostic test; Beef cattle; Diagnostic accuracy; Confidence interval; Disease; Internal medicine; Veterinary medicine; Predictive value; Immunology; Animal science","routes":{"ca_aff":true,"ca_fund":false,"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":[0.01100247,0.0005779064,0.0006613129,0.001135801,0.0002708448,0.001079889,0.0007496933,0.001151314,0.0005673982],"category_scores_gemma":[0.03455307,0.0004788551,0.0007136342,0.0003696044,0.0005659391,0.0007454999,0.0007241109,0.0006889806,0.000127355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000904695,"about_ca_system_score_gemma":0.0008684869,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006536125,"about_ca_topic_score_gemma":0.006296919,"domain_scores_codex":[0.9975249,0.001207821,0.0001992734,0.0004293696,0.0004244539,0.0002141802],"domain_scores_gemma":[0.9445622,0.0475383,0.003456086,0.0008357362,0.002819627,0.0007880871],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004873665,0.0006353881,0.5219575,0.0002307517,0.0006803646,0.0002833567,0.0002984478,0.3457141,0.01147899,0.001646673,0.0006347177,0.111566],"study_design_scores_gemma":[0.00005590529,0.0004466056,0.08451828,0.00003280231,0.0001690654,0.0001299488,0.00007208505,0.9111668,0.002253552,0.001005871,0.0001149071,0.0000340852],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9540496,0.0006462884,0.04403177,0.0001984377,0.00001536533,0.00003967145,0.0001774827,0.00007309344,0.0007682341],"genre_scores_gemma":[0.9957671,0.00007739613,0.003786264,0.00002257468,0.00001244491,0.000008213182,0.000167553,0.000005342707,0.0001531878],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01100247,"threshold_uncertainty_score":0.05818731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1294291483478594,"score_gpt":0.4399397306436561,"score_spread":0.3105105822957967,"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."}}