{"id":"W4210698103","doi":"10.1093/tas/txac006","title":"Immuno-phenotyping of Canadian beef cattle: adaptation of the high immune response methodology for utilization in beef cattle","year":2022,"lang":"en","type":"article","venue":"Translational Animal Science","topic":"Microbial infections and disease research","field":"Immunology and Microbiology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Arrell Food Institute, University of Guelph; University of Guelph; Ministry of Agriculture, Food and Rural Affairs; Ontario Ministry of Agriculture, Food and Rural Affairs; Beef Farmers of Ontario; Canada First Research Excellence Fund","keywords":"Beef cattle; Breed; Biology; Animal science; Immune system; Dairy cattle; Veterinary medicine; Biotechnology; Immunology; Medicine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002076927,0.00006711565,0.0001387653,0.0005879196,0.0006045436,0.000005598381,0.0003012628,0.00004874532,0.0006531052],"category_scores_gemma":[0.0003365377,0.00006027695,0.0000660476,0.001592959,0.0005487073,0.0001023017,0.00004750193,0.0001406056,0.000002600722],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001079482,"about_ca_system_score_gemma":0.001373201,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.07783685,"about_ca_topic_score_gemma":0.01967725,"domain_scores_codex":[0.998667,0.0004857615,0.0003037087,0.0001962925,0.00009369652,0.000253524],"domain_scores_gemma":[0.9989999,0.0005511919,0.0001019208,0.0001343851,0.0001905208,0.00002209226],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0009536583,0.00007280966,0.001309098,0.00001245535,0.00001136323,9.719819e-8,0.0009960982,0.00606844,0.9689808,0.01987462,0.00001986803,0.00170065],"study_design_scores_gemma":[0.00108631,0.0002615627,0.850081,0.00001867469,0.00002085474,0.00001562201,0.0008120077,0.001066236,0.1425612,0.001325785,0.002624591,0.0001261854],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953401,0.0009019321,0.001623339,0.001029751,0.0002042115,0.0003994438,0.0003950321,0.000005537655,0.0001006229],"genre_scores_gemma":[0.9993122,0.000009255264,0.0004359924,0.00002592379,0.000004864503,0.00004485298,0.00006935882,0.000005079972,0.00009245337],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8487719,"threshold_uncertainty_score":0.9982111,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1085656189117763,"score_gpt":0.3355722222196979,"score_spread":0.2270066033079216,"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."}}