{"id":"W4388653082","doi":"10.1021/acs.bioconjchem.3c00357","title":"Rapid Access to Potent Bispecific T Cell Engagers Using Biogenic Tyrosine Click Chemistry","year":2023,"lang":"en","type":"article","venue":"Bioconjugate Chemistry","topic":"Monoclonal and Polyclonal Antibodies Research","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"H2020 Marie Skłodowska-Curie Actions; Wageningen University Fund; Engineering and Physical Sciences Research Council; Centre National de la Recherche Scientifique; Wageningen University and Research; Université de Strasbourg; University College London; Agence Nationale de la Recherche; Queen's University Belfast; European Commission; Queen's University","keywords":"Chemistry; Bispecific antibody; Antigen; Click chemistry; Antibody; Computational biology; Modular design; Construct (python library); Combinatorial chemistry; Biochemistry; Monoclonal antibody; Computer science; Immunology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003770411,0.0005449516,0.0002196859,0.0002236604,0.00009720453,0.0002789898,0.0002613963,0.0004228488,0.00123206],"category_scores_gemma":[0.0002140175,0.0001533081,0.0002310132,0.0002091137,0.0002126932,0.0003628368,0.0004065824,0.0005528956,0.0004374324],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002128561,"about_ca_system_score_gemma":0.0001499028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001522646,"about_ca_topic_score_gemma":0.0003109456,"domain_scores_codex":[0.9997999,0.00003334149,0.00001489898,0.0000527969,0.00005446075,0.00004454909],"domain_scores_gemma":[0.9999152,0.00001951359,0.00002872007,0.00000820947,0.00001113093,0.00001722543],"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":[0.00003387477,0.0000260556,0.00006167498,0.00005668728,0.000006710228,0.00007859755,0.00003028874,0.0002359232,0.9954149,0.0006134043,0.00009331955,0.003348695],"study_design_scores_gemma":[0.00001096018,0.0001594386,0.0002001087,0.000002094159,0.000006471653,0.0001455516,0.000005578733,0.0009385633,0.9963173,0.00006369366,0.00214492,0.000005419938],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8894281,0.003038648,0.09992757,0.0002299585,0.00007500942,0.0001906448,0.0003529631,0.0006047891,0.006152392],"genre_scores_gemma":[0.9726321,0.001700596,0.02182585,0.0001265705,0.00002277158,0.0001000603,0.0003168281,0.00005428649,0.003220948],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00123206,"threshold_uncertainty_score":0.004121661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09623948232885196,"score_gpt":0.3468809702756837,"score_spread":0.2506414879468317,"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."}}