{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007160171,0.00006233528,0.0002113611,0.0001621579,0.00002760273,0.00000637465,0.00002886053,0.00004825175,0.00004694066],"category_scores_gemma":[0.0002830949,0.00005328845,0.00002335264,0.0002266333,0.0001007363,0.00003052806,0.00006027761,0.00007688777,0.00000757415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000100814,"about_ca_system_score_gemma":0.0001587945,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000045795,"about_ca_topic_score_gemma":0.00002022291,"domain_scores_codex":[0.999316,0.000101939,0.0001865978,0.0001725412,0.00009333594,0.0001296076],"domain_scores_gemma":[0.9992915,0.0004716485,0.00002734226,0.00003430444,0.0001117363,0.00006348398],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007405485,0.0001174227,0.9275978,0.00007209044,0.00003130801,0.0000341224,0.0001220023,0.00006999581,0.0664314,0.001642854,0.00003697601,0.00310344],"study_design_scores_gemma":[0.0004034019,0.0004824961,0.9603361,0.00007309796,0.000008418581,0.0001324704,0.00003615803,0.004292471,0.03001967,0.003809664,0.0003415447,0.00006450518],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979177,0.0002344144,0.0001559843,0.001389598,0.00002048726,0.0001077548,0.00002326266,0.00000818166,0.0001426255],"genre_scores_gemma":[0.9843816,0.00003725371,0.01485983,0.0003970671,0.00002067695,0.000005978929,0.00006023627,0.00000457515,0.0002328207],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03641173,"threshold_uncertainty_score":0.217304,"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."}}