{"id":"W811006216","doi":"10.1016/j.mimet.2015.06.018","title":"Expeditious screening of candidate proteins for microbial vaccines","year":2015,"lang":"en","type":"article","venue":"Journal of Microbiological Methods","topic":"Microbial infections and disease research","field":"Immunology and Microbiology","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Genome Alberta; Alberta Livestock and Meat Agency","keywords":"Biology; Immunogenicity; In silico; Recombinant DNA; Computational biology; Gene; Protein subunit; Antigenicity; Candidate gene; Molecular biology; Antibody; Genetics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005076864,0.0006323367,0.000454004,0.0004477902,0.0002412802,0.0004548381,0.0004086042,0.0004053303,0.001718851],"category_scores_gemma":[0.0008535002,0.0002521966,0.0004608033,0.0003513445,0.000244463,0.0003205772,0.0004811374,0.0009530531,0.00101933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002373577,"about_ca_system_score_gemma":0.0004137945,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004444467,"about_ca_topic_score_gemma":0.001014077,"domain_scores_codex":[0.9995564,0.0001430415,0.00002264276,0.00005673723,0.0001436326,0.00007760668],"domain_scores_gemma":[0.9996963,0.0001248049,0.00002949353,0.00004937931,0.00007076566,0.00002938543],"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":[0.0001265807,0.00008691109,0.0002030977,0.00005249761,0.000008866604,0.00006115804,0.00002478119,0.0003242247,0.9928257,0.0001897587,0.0001477853,0.005948497],"study_design_scores_gemma":[0.00003991955,0.0004896009,0.0009878475,0.0000100351,0.00004218324,0.0003078633,0.00004492438,0.002293968,0.9903657,0.0001982285,0.005211989,0.000007815441],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8471987,0.001691176,0.1424888,0.0004606966,0.00009609066,0.0009866299,0.0008851712,0.000418923,0.005773933],"genre_scores_gemma":[0.8742201,0.001836497,0.1122016,0.0002956757,0.00003001207,0.0005035507,0.002455069,0.0001421002,0.008315369],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001718851,"threshold_uncertainty_score":0.00575012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.106069484302009,"score_gpt":0.4198459702100777,"score_spread":0.3137764859080688,"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."}}