{"id":"W4311279618","doi":"10.1039/d2ra05630e","title":"Tag-free, specific conjugation of glycosylated IgG1 antibodies using microbial transglutaminase","year":2022,"lang":"en","type":"article","venue":"RSC Advances","topic":"Monoclonal and Polyclonal Antibodies Research","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; PROTEO; Centre in Green Chemistry and Catalysis","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec – Nature et technologies; Université de Montréal; Centre in Green Chemistry and Catalysis; Fonds Québécois de la Recherche sur la Nature et les Technologies; Bundesministerium für Bildung und Forschung; Canada Foundation for Innovation","keywords":"Conjugate; Chemistry; Fluorophore; Conjugated system; Antibody-drug conjugate; Antibody; Biochemistry; Combinatorial chemistry; Pentapeptide repeat; Fluorescence; Stereochemistry; Peptide; Monoclonal antibody; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002089168,0.0003833313,0.0002289564,0.000159259,0.00009304837,0.0002913084,0.0002796646,0.0004268366,0.0004350552],"category_scores_gemma":[0.0001719395,0.0001224041,0.0002489513,0.0001679696,0.0002015265,0.0002259873,0.0003123912,0.0006142225,0.0002876609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003403667,"about_ca_system_score_gemma":0.0001791333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004923571,"about_ca_topic_score_gemma":0.0007450876,"domain_scores_codex":[0.9998322,0.00002493387,0.00001495159,0.00004048101,0.00005376613,0.00003378498],"domain_scores_gemma":[0.9999061,0.00001145475,0.00003564305,0.00001485389,0.00001329101,0.00001862011],"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":[0.0000162758,0.00001280334,0.00008549936,0.00002435835,0.00000483361,0.00005860262,0.000012605,0.00009829444,0.9974235,0.0001609889,0.0000257003,0.002076483],"study_design_scores_gemma":[0.000003447971,0.00009077459,0.000292064,0.000001548766,0.000005395455,0.0001621795,0.000002967907,0.0003681896,0.9977251,0.00002332014,0.001322377,0.00000270952],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9088252,0.002399582,0.08551151,0.000181745,0.00005472274,0.0001342033,0.0003030269,0.0002852155,0.002304837],"genre_scores_gemma":[0.9717057,0.0009866862,0.02500063,0.00009246541,0.00001160333,0.00003663723,0.0002856323,0.00002918296,0.001851558],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0004923571,"threshold_uncertainty_score":0.002469599,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03265323233847862,"score_gpt":0.313727708436338,"score_spread":0.2810744760978594,"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."}}