{"id":"W2476649705","doi":"10.1126/sciadv.1600692","title":"Protein engineering by highly parallel screening of computationally designed variants","year":2016,"lang":"en","type":"article","venue":"Science Advances","topic":"Monoclonal and Polyclonal Antibodies Research","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Protein engineering; Computer science; Protein design; Computational biology; Protein structure; Biology; Biochemistry","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":[0.001068243,0.0008610717,0.001130244,0.0005491371,0.0004266553,0.0008389661,0.0007541497,0.0003652841,0.00122048],"category_scores_gemma":[0.001077592,0.0003222223,0.0004565872,0.000770762,0.0003892992,0.0004487066,0.0009014043,0.0006689892,0.0006065808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008955076,"about_ca_system_score_gemma":0.0008818985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006085551,"about_ca_topic_score_gemma":0.001359444,"domain_scores_codex":[0.9993296,0.0001219204,0.00004999132,0.0001688418,0.0002573307,0.00007230565],"domain_scores_gemma":[0.9997066,0.0001166933,0.00004258841,0.00006387878,0.0000498231,0.00002053029],"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":[0.0006378224,0.0006206511,0.002043308,0.0002631552,0.0001108563,0.0002864578,0.00008931232,0.1038695,0.7567012,0.008435845,0.001056173,0.1258856],"study_design_scores_gemma":[0.0001473743,0.0005827057,0.0006743137,0.00000699713,0.00007275334,0.0002962023,0.00003357745,0.4242186,0.5670826,0.00215373,0.004692091,0.00003898296],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.564563,0.000590815,0.4252251,0.0001752632,0.00005591036,0.0004720693,0.0003033864,0.002446609,0.006167802],"genre_scores_gemma":[0.7126576,0.0004740468,0.2834955,0.0001095787,0.00001336703,0.0004535617,0.0004767367,0.0002326818,0.00208699],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00122048,"threshold_uncertainty_score":0.006497443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01919320719201969,"score_gpt":0.3043172599865023,"score_spread":0.2851240527944826,"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."}}