{"id":"W4410871695","doi":"10.1111/jfd.14151","title":"Serum Biomarkers in Atlantic Salmon for Differential Diagnosis of Cardiomyopathy Syndrome and Pancreas Disease: Proteomic Identification of Serum Fibrinogen to Enhance Troponin Immunoassay as Optimal Diagnostic Approach","year":2025,"lang":"en","type":"article","venue":"Journal of Fish Diseases","topic":"Aquaculture disease management and microbiota","field":"Immunology and Microbiology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cooke Aquaculture (Canada)","funders":"Biotechnology and Biological Sciences Research Council; Directorate for Biological Sciences; Scottish Aquaculture Innovation Centre; University of Glasgow","keywords":"Biology; Fibrinogen; Cardiomyopathy; Myocarditis; Salmo; Biomarker; Internal medicine; Troponin I; Fishery; Heart failure; Medicine; Fish <Actinopterygii>; Biochemistry","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":[0.0009271521,0.0005374096,0.0003722876,0.0009288166,0.0001922486,0.00051566,0.0001559834,0.000495429,0.0005044069],"category_scores_gemma":[0.0006291997,0.0002054483,0.0002700159,0.0004758861,0.000233997,0.0002060683,0.0003368641,0.0003433762,0.0002472581],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002060563,"about_ca_system_score_gemma":0.0003228296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001270279,"about_ca_topic_score_gemma":0.003165535,"domain_scores_codex":[0.9997242,0.00006390611,0.00003497824,0.0000564648,0.00008470238,0.00003573223],"domain_scores_gemma":[0.9997508,0.0000369992,0.00007550666,0.00000972778,0.00008670738,0.00004019582],"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":[0.001074965,0.0001348141,0.4033668,0.0003631636,0.0001142694,0.0004545072,0.0002760598,0.0001637252,0.5675485,0.00007877999,0.0003690186,0.02605543],"study_design_scores_gemma":[0.00003685374,0.001818324,0.9042694,0.0001521648,0.0002177464,0.001885066,0.0008070497,0.003076122,0.08521124,0.0001811963,0.002311844,0.00003296127],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.991253,0.0029948,0.003973204,0.0001786293,0.00004539177,0.00007049899,0.0003723531,0.00003989983,0.001072243],"genre_scores_gemma":[0.9840503,0.001482994,0.01245905,0.0003098594,0.00002826038,0.00007198201,0.0004649918,0.000009205441,0.00112335],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001270279,"threshold_uncertainty_score":0.004903316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004290438272126005,"score_gpt":0.2385342388180381,"score_spread":0.2342438005459122,"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."}}