{"id":"W3139465356","doi":"10.1371/journal.pcbi.1008751","title":"Parameters and determinants of responses to selection in antibody libraries","year":2021,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Monoclonal and Polyclonal Antibodies Research","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Fondation pour la Recherche Médicale; CHIST-ERA; Agence Nationale de la Recherche","keywords":"Affinity maturation; Germline; Computational biology; Selection (genetic algorithm); Phage display; Biology; Genome; Antibody; Somatic cell; Negative selection; Genetics; Gene; Computer science","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":[0.001466207,0.0004237482,0.000513241,0.0006363143,0.0001551861,0.001041183,0.0004381738,0.0007041996,0.001439048],"category_scores_gemma":[0.01164333,0.0002460174,0.0002452394,0.0005348527,0.0004447938,0.0005362,0.0005110572,0.0007731892,0.0002287347],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006018095,"about_ca_system_score_gemma":0.0002243796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005323681,"about_ca_topic_score_gemma":0.0003436731,"domain_scores_codex":[0.998646,0.0004466184,0.0001100091,0.0002753056,0.000323726,0.0001984223],"domain_scores_gemma":[0.9892588,0.008345188,0.001063691,0.0004195567,0.0005236513,0.0003890719],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006693955,0.0002024314,0.01570733,0.0001691091,0.00008786115,0.00009813713,0.00009796004,0.04128084,0.9324621,0.0006585314,0.0001364896,0.008429853],"study_design_scores_gemma":[0.00006604567,0.001736696,0.05069891,0.00002034287,0.00008493139,0.0003577099,0.0001927734,0.1344828,0.8101862,0.001411478,0.0006647001,0.00009738081],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9907141,0.0001440819,0.008106726,0.00006869841,0.000006627774,0.00002597493,0.0001786715,0.0001098676,0.000645256],"genre_scores_gemma":[0.9979904,0.00006542483,0.001434925,0.0000350121,0.000003141296,0.00003312984,0.0002298206,0.00002719191,0.0001810221],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001466207,"threshold_uncertainty_score":0.007754087,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05158359495265716,"score_gpt":0.37121061325859,"score_spread":0.3196270183059329,"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."}}