{"id":"W3214668463","doi":"10.1002/prot.26280","title":"Functional antibody characterization via direct structural analysis and information‐driven protein–protein docking","year":2021,"lang":"en","type":"article","venue":"Proteins Structure Function and Bioinformatics","topic":"Monoclonal and Polyclonal Antibodies Research","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Group for Research in Decision Analysis","funders":"","keywords":"In silico; Computational biology; Docking (animal); Antibody; Mutagenesis; In vitro; Chemistry; Vascular endothelial growth factor; Kinase insert domain receptor; Cell biology; VEGF receptors; Biology; Mutant; Vascular endothelial growth factor A; Cancer research; Biochemistry; Immunology; Medicine","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":[0.0001221207,0.0002874545,0.0004352915,0.0004450093,0.0004395689,0.0002409556,0.00005151348,0.0001884477,0.0005433948],"category_scores_gemma":[0.00009865397,0.0002189672,0.0001281406,0.0009326614,0.0001311179,0.001223816,0.0001325126,0.0003592866,0.00001460629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004622482,"about_ca_system_score_gemma":0.0001282757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003997329,"about_ca_topic_score_gemma":0.00001860427,"domain_scores_codex":[0.9982239,0.00005239619,0.0005668989,0.0002346187,0.0005995306,0.0003226746],"domain_scores_gemma":[0.9988065,0.0000209884,0.000241193,0.0002303336,0.0004606367,0.000240367],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00139546,0.00006314716,0.0804656,0.002528961,0.00207375,0.00002153765,0.0008844508,0.00008115012,0.7975691,0.003706521,0.00004134232,0.111169],"study_design_scores_gemma":[0.002195802,0.0005141713,0.867247,0.0002033869,0.0007641555,0.0004214912,0.0002657739,0.07751241,0.03699836,0.0006632338,0.01258982,0.0006243956],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.940845,0.0001103088,0.05558212,0.001125505,0.0001419291,0.001046509,0.0002229511,0.00009822535,0.0008275284],"genre_scores_gemma":[0.9816422,0.00006312784,0.0105891,0.0005995531,0.0002165621,0.00003660263,0.006026081,0.00001393347,0.0008128009],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7867814,"threshold_uncertainty_score":0.8929224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009092878569124028,"score_gpt":0.2478879446607479,"score_spread":0.2387950660916239,"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."}}