{"id":"W3130453010","doi":"10.1101/2021.02.20.432100","title":"DNA-Encoded Multivalent Display of Protein Tetramers on Phage: Synthesis and <i>In Vivo</i> Aplications","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Monoclonal and Polyclonal Antibodies Research","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Canadian Glycomics Network; Natural Sciences and Engineering Research Council of Canada; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Tel Aviv University; Alberta Innovates; Fundação de Amparo à Pesquisa do Estado de São Paulo; University of Alberta","keywords":"Phage display; Phagemid; Biology; DNA; Molecular biology; Peptide library; DNA sequencing; Fusion protein; Bacteriophage; Biochemistry; Peptide sequence; Peptide; Escherichia coli; Gene","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":[0.0001938378,0.0003076492,0.0001492173,0.0001586088,0.0001309001,0.000275651,0.0002500501,0.0002905714,0.0005921865],"category_scores_gemma":[0.0001227867,0.0001354953,0.0002065692,0.0001765258,0.0001557875,0.0001405916,0.0002202594,0.0004610619,0.0003302532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002497361,"about_ca_system_score_gemma":0.00009153073,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004326762,"about_ca_topic_score_gemma":0.0003655271,"domain_scores_codex":[0.9998816,0.00001925511,0.000010111,0.00003598547,0.00003024261,0.00002274207],"domain_scores_gemma":[0.9998887,0.00002318831,0.00003245574,0.00001494214,0.0000178371,0.00002288495],"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":[0.00000972052,0.000006680682,0.00002767637,0.000007162276,0.0000010576,0.000009008919,0.000006501908,0.00003097305,0.9995232,0.00003412137,0.000009320306,0.0003345144],"study_design_scores_gemma":[0.00000146078,0.00003473816,0.0001837771,7.610382e-7,0.000001905896,0.00002696287,0.000002727887,0.0004713134,0.9988589,0.000009067869,0.0004070158,0.000001359583],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9662541,0.0004168538,0.03129434,0.00006100547,0.00002294831,0.00005502766,0.0003361268,0.0002752843,0.001284498],"genre_scores_gemma":[0.9782766,0.0003369436,0.01651236,0.00005052904,0.00000664415,0.00005561477,0.0005472386,0.0000890093,0.004125032],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005921865,"threshold_uncertainty_score":0.00198102,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01937563223047178,"score_gpt":0.2663895152489094,"score_spread":0.2470138830184376,"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."}}