{"id":"W124230207","doi":"10.1007/978-1-62703-586-6_14","title":"Phage Display Technology for Human Monoclonal Antibodies","year":2013,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Monoclonal and Polyclonal Antibodies Research","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Tufts University School of Medicine; Centro Singular de Investigación de Galicia; Uppsala Universitet; Technische Universität Braunschweig; Japan Society for the Promotion of Science; National Institute of Diabetes and Digestive and Kidney Diseases; University of Tokyo; Università degli Studi del Piemonte Orientale; Hebrew University of Jerusalem; Eidgenössische Technische Hochschule Zürich; University of Toronto; Chugai Pharmaceutical","keywords":"Phage display; Monoclonal antibody; Phagemid; Selection (genetic algorithm); Antibody; Biology; Computational biology; Effector; Function (biology); Negative selection; Hybridoma technology; Gene; Genetics; Bacteriophage; Computer science; Immunology; Escherichia coli; Artificial intelligence; Genome","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000641794,0.0002221764,0.0005482393,0.0004834316,0.0001002446,0.00001308342,0.0002427693,0.0003271809,0.0002785984],"category_scores_gemma":[0.0004265359,0.000171701,0.0001747393,0.0003284463,0.0004597111,0.00002885037,0.0001848747,0.0003757676,0.00004525357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003904045,"about_ca_system_score_gemma":0.00004894096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001877472,"about_ca_topic_score_gemma":0.00001145103,"domain_scores_codex":[0.9981377,0.0002904328,0.0003853638,0.0004681695,0.00009808944,0.0006202083],"domain_scores_gemma":[0.9990646,0.000275636,0.00006515797,0.0003359986,0.0001455881,0.0001130397],"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":[0.00006362909,0.0001078753,0.03390485,0.00007534377,0.00007703742,0.00004267134,0.00002732464,0.000001020199,0.8793955,0.04662434,0.0001840692,0.0394963],"study_design_scores_gemma":[0.002390333,0.001532454,0.0206057,0.00007843208,0.00005708865,0.0002050982,0.0001095194,0.001045758,0.7286226,0.2030929,0.04179473,0.0004653018],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6004429,0.001816864,0.3882874,0.005137614,0.0001497113,0.001151683,0.00002045995,0.00006825211,0.002925119],"genre_scores_gemma":[0.08524849,0.000081133,0.9109444,0.0008067064,0.0001024422,0.0004688299,0.00009425529,0.00003505702,0.002218712],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5226569,"threshold_uncertainty_score":0.7001765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04003425364022478,"score_gpt":0.4734810811312822,"score_spread":0.4334468274910574,"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."}}