{"id":"W2903567932","doi":"10.1111/jfd.12933","title":"Bayesian latent class analysis of <scp>ELISA</scp> and <scp>RT</scp>‐<scp>rPCR</scp> diagnostic accuracy for subclinical <i>Renibacterium salmoninarum</i> infection in Atlantic salmon (<i>Salmo salar</i>) broodstock","year":2018,"lang":"en","type":"article","venue":"Journal of Fish Diseases","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Grieg Seafood (Canada); BC Centre for Aquatic Health Sciences; University of Prince Edward Island","funders":"Canada Excellence Research Chairs, Government of Canada","keywords":"Broodstock; Biology; Salmo; Aquaculture; Fishery; Fish <Actinopterygii>","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.01325682,0.0004715898,0.0005542625,0.001187922,0.00057085,0.001418716,0.0008326025,0.0006192924,0.001369134],"category_scores_gemma":[0.01954598,0.0004351991,0.001345386,0.00052207,0.0008698102,0.0006269559,0.0008524574,0.0008700404,0.0003171836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001639576,"about_ca_system_score_gemma":0.001211859,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03017254,"about_ca_topic_score_gemma":0.02121119,"domain_scores_codex":[0.9961615,0.002042054,0.0002273177,0.000730989,0.0005096108,0.0003285889],"domain_scores_gemma":[0.9778305,0.01498476,0.003207031,0.001413759,0.002126137,0.0004379327],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003193285,0.0004407949,0.831954,0.0001178574,0.001007711,0.0001280558,0.0008469928,0.079674,0.01189322,0.003640754,0.001253202,0.06585021],"study_design_scores_gemma":[0.00006554243,0.0003265272,0.2895346,0.00004106805,0.0002680715,0.0001360766,0.0002589163,0.7025672,0.003274211,0.002827112,0.0006129007,0.00008773643],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9641621,0.0001474216,0.03404449,0.0001418902,0.00001042628,0.00006492551,0.0006205172,0.0001143015,0.0006940188],"genre_scores_gemma":[0.9932398,0.00002908809,0.005507026,0.00001841141,0.000006819762,0.00002929527,0.00085015,0.00001746137,0.0003018811],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03017254,"threshold_uncertainty_score":0.07010961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01243086061114206,"score_gpt":0.2582025154959024,"score_spread":0.2457716548847603,"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."}}