{"id":"W4213304877","doi":"10.1007/978-1-0716-2075-5_14","title":"Humanization of Camelid Single-Domain Antibodies","year":2022,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Monoclonal and Polyclonal Antibodies Research","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; National Research Council Canada","funders":"","keywords":"Single-domain antibody; Prioritization; Immunogenicity; Complementarity (molecular biology); Computational biology; Computer science; Antibody; Domain (mathematical analysis); Monoclonal antibody; Complementarity determining region; Biology; Engineering; Immunology; Genetics; Mathematics; Management 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":[0.0007628912,0.000681754,0.0004362745,0.0008103897,0.0005386727,0.0007975795,0.001128529,0.0008472205,0.005579727],"category_scores_gemma":[0.0006503723,0.0004443444,0.0009821198,0.0003916885,0.0003331384,0.0003981212,0.0005354775,0.001621289,0.003523758],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009219614,"about_ca_system_score_gemma":0.0002659847,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006766372,"about_ca_topic_score_gemma":0.0007099119,"domain_scores_codex":[0.9993862,0.00008827772,0.00007523723,0.0001789214,0.000136171,0.0001351691],"domain_scores_gemma":[0.9994842,0.00009407424,0.00006483836,0.0001657736,0.0001096517,0.00008147101],"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":[0.0001482853,0.00003757538,0.0001484478,0.00007948323,0.00001974068,0.00008506593,0.00006295681,0.00009205016,0.9949031,0.0007130697,0.0007486106,0.002961761],"study_design_scores_gemma":[0.00004428113,0.000144449,0.001936152,0.00001978026,0.00004088377,0.0003399493,0.00002940064,0.0008055069,0.9522794,0.000123755,0.0442258,0.00001060695],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8047564,0.005239277,0.139852,0.002504243,0.001214372,0.001815253,0.0171874,0.00237059,0.02506047],"genre_scores_gemma":[0.8175398,0.003618096,0.09514081,0.001962248,0.0003313041,0.001156922,0.0462318,0.0007417248,0.03327742],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.005579727,"threshold_uncertainty_score":0.01866609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04767506697101619,"score_gpt":0.4382036851410437,"score_spread":0.3905286181700275,"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."}}