{"id":"W3212275832","doi":"10.3389/fimmu.2021.775678","title":"A Strategy for Efficient Preparation of Genus-Specific Diagnostic Antibodies for Snakebites","year":2021,"lang":"en","type":"article","venue":"Frontiers in Immunology","topic":"Venomous Animal Envenomation and Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; St. Michael's Hospital","funders":"National Natural Science Foundation of China; Chinese Academy of Sciences; National Science Foundation","keywords":"Snake venom; Polyclonal antibodies; Epitope; Venom; Antivenom; Immunogenicity; Antigen; Antibody; Genus; Monoclonal antibody; Biology; Envenomation; Immunology; Medicine; Zoology; Ecology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009247261,0.00008775981,0.0002005758,0.00004800297,0.00005638907,0.00000709128,0.00007213485,0.00009697119,0.000003764066],"category_scores_gemma":[0.000278183,0.00009064903,0.00008074585,0.00005685984,0.00009399268,0.000001828583,0.00003716806,0.00002831684,5.828628e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001441645,"about_ca_system_score_gemma":0.00005542498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002251154,"about_ca_topic_score_gemma":0.00001968219,"domain_scores_codex":[0.9993275,0.00003433558,0.0002268191,0.0002171409,0.00003163649,0.0001625907],"domain_scores_gemma":[0.9995657,0.00005384491,0.0000807075,0.0001451966,0.0001440264,0.00001050709],"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":[0.001693896,0.0007870232,0.01384467,0.0002779634,0.0006722222,0.000006360575,0.001106663,0.007867998,0.9074559,0.009816241,0.0368285,0.01964255],"study_design_scores_gemma":[0.00534986,0.0034835,0.04528058,0.00007328992,0.00007818612,0.00002718708,0.004699667,0.003539905,0.619989,0.002613169,0.3142368,0.0006288651],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8623946,0.03553524,0.1004306,0.0001190838,0.0005847553,0.0004821477,0.00009244561,0.000007110933,0.0003540365],"genre_scores_gemma":[0.9871501,0.001623169,0.01041673,0.00002774587,0.00005468833,0.0001441941,0.0002505551,0.00001149856,0.0003212591],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2874669,"threshold_uncertainty_score":0.369656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01502089042468869,"score_gpt":0.270118106675628,"score_spread":0.2550972162509393,"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."}}