{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00162267,0.0003339575,0.0002095372,0.001200978,0.0006852196,0.0004530218,0.0005649725,0.0002506889,0.0009560005],"category_scores_gemma":[0.001056158,0.000176361,0.0002543229,0.000902992,0.0003981774,0.0001656207,0.0002985229,0.0004041712,0.0001680934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002659042,"about_ca_system_score_gemma":0.001638017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3689393,"about_ca_topic_score_gemma":0.6252285,"domain_scores_codex":[0.9989513,0.0002279891,0.00003772395,0.0002195645,0.0003898703,0.0001734455],"domain_scores_gemma":[0.9989445,0.0001705645,0.0002877328,0.00009065648,0.000374183,0.0001325157],"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":[0.000730871,0.0002030353,0.260074,0.0002018056,0.00009251362,0.00017124,0.0009794364,0.0007718226,0.6959056,0.0003667862,0.000400298,0.04010263],"study_design_scores_gemma":[0.00001035602,0.0004453019,0.9687244,0.00001101413,0.00003866106,0.0001723049,0.0002714034,0.0008367263,0.02792172,0.00002950449,0.001521064,0.00001752898],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9870346,0.0004507436,0.009315117,0.00003532285,0.00001081902,0.0001548551,0.0007015204,0.0000651135,0.002231934],"genre_scores_gemma":[0.9763098,0.000351298,0.01986596,0.0001005098,0.000009090504,0.0001191057,0.0007957991,0.0000289657,0.002419543],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3689393,"threshold_uncertainty_score":0.7335837,"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."}}