{"id":"W2040153440","doi":"10.1021/pr049840t","title":"Application of Isotope Coded Affinity Tag (ICAT) Analysis for the Identification of Differentially Expressed Proteins Following Infection of Atlantic Salmon (<i>Salmo </i><i>s</i><i>alar)</i> with Infectious Hematopoietic Necrosis Virus (IHNV) or <i>Renibacterium </i><i>s</i><i>almoninarum</i> (BKD)","year":2005,"lang":"en","type":"article","venue":"Journal of Proteome Research","topic":"Aquaculture disease management and microbiota","field":"Immunology and Microbiology","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"Genome British Columbia; University of Victoria","funders":"","keywords":"Salmo; Infectious hematopoietic necrosis virus; Biology; Proteomics; Haematopoiesis; Molecular biology; Computational biology; Biochemistry; Gene; Cell biology; Fishery; Fish <Actinopterygii>; Rainbow trout; Stem cell","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":[0.0002152302,0.0003963656,0.0003164095,0.0005150511,0.0003005585,0.0003449826,0.0002185111,0.0004010092,0.0005661697],"category_scores_gemma":[0.0002650708,0.000145764,0.0004270365,0.0003650145,0.0003089663,0.0001840406,0.000243937,0.0004440782,0.0003108332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002643263,"about_ca_system_score_gemma":0.000312869,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002206312,"about_ca_topic_score_gemma":0.003616718,"domain_scores_codex":[0.9998537,0.00001385368,0.00001066435,0.00005000686,0.00003999195,0.00003178678],"domain_scores_gemma":[0.9998241,0.000034983,0.00003522004,0.00001667909,0.00005442796,0.00003463831],"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":[0.00004894005,0.000009184258,0.0008601555,0.00002407431,0.000007713428,0.00003482437,0.00001700276,0.00002021762,0.9979184,0.00001859017,0.00001629417,0.001024675],"study_design_scores_gemma":[0.00001466297,0.0004280124,0.06931182,0.00000980707,0.00008313335,0.001355508,0.0001762268,0.003930006,0.9222284,0.00009233493,0.002344693,0.00002546136],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9779229,0.001814591,0.01772478,0.0002436808,0.00006815876,0.00006250682,0.0007253499,0.0001183273,0.001319668],"genre_scores_gemma":[0.9508399,0.002033059,0.04101879,0.0004684077,0.00003646434,0.0000957791,0.002191415,0.00005377693,0.0032624],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002206312,"threshold_uncertainty_score":0.004386961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02300334029474501,"score_gpt":0.2951052180273879,"score_spread":0.2721018777326429,"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."}}