{"id":"W2903331125","doi":"10.1016/j.isci.2018.11.038","title":"In Silico Engineering of Synthetic Binding Proteins from Random Amino Acid Sequences","year":2018,"lang":"en","type":"article","venue":"iScience","topic":"Biochemical and Structural Characterization","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; University of Regina; Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"In silico; Synthetic biology; Computational biology; Protein engineering; Directed Molecular Evolution; Protein design; Biology; Directed evolution; Biochemistry; Gene; Protein structure; Mutant","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006259518,0.00005852256,0.00007131822,0.00002436474,0.00002171648,0.000009705822,0.0001479791,0.00005244067,0.00001745109],"category_scores_gemma":[0.00009897354,0.00004693629,0.00001949101,0.0001212255,0.0001355803,0.000007695297,0.00004550826,0.00003026932,0.000003145589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005956609,"about_ca_system_score_gemma":0.00001793209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003202589,"about_ca_topic_score_gemma":0.000007928775,"domain_scores_codex":[0.99951,0.000009609009,0.0001105236,0.0001826026,0.00007633267,0.0001109437],"domain_scores_gemma":[0.9998003,0.000005636843,0.00003921458,0.000104352,0.00002487158,0.00002565038],"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":[0.00001622127,0.00000424106,0.001037149,0.000004427379,0.000001367178,3.792009e-7,0.00005611064,0.000003778474,0.998224,0.00001214802,0.000003548657,0.0006366138],"study_design_scores_gemma":[0.0001468002,0.00005467264,0.00463369,0.00002209188,0.000001349028,0.000001922365,0.00001069097,0.0004054777,0.9944454,0.00005104321,0.0001625861,0.00006429839],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986629,0.00009858839,0.0009225903,0.00007113318,0.00009954676,0.00007245831,0.00001130883,0.000003886819,0.00005756786],"genre_scores_gemma":[0.9990622,0.00001114693,0.0007564292,0.00002839959,0.00009434253,0.000005372388,0.00001094336,0.000002820413,0.00002828761],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003778637,"threshold_uncertainty_score":0.1914006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007020170193330768,"score_gpt":0.2180484081092271,"score_spread":0.2110282379158964,"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."}}