{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003415587,0.00008003597,0.000144926,0.0001096499,0.00009041734,0.00001136658,0.0001935865,0.00001764269,0.00004558875],"category_scores_gemma":[0.000215271,0.00004726896,0.00003159845,0.0003604722,0.0004013154,0.0003803513,0.00005043466,0.00004773406,0.00001535843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000202873,"about_ca_system_score_gemma":0.0001423895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001517337,"about_ca_topic_score_gemma":8.830631e-7,"domain_scores_codex":[0.9986711,0.00001137179,0.0001717436,0.0002208404,0.0006460196,0.0002789834],"domain_scores_gemma":[0.9994252,0.0001137941,0.00005564533,0.0001015592,0.0001715827,0.0001321861],"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":[0.0001056433,0.00003244106,0.002259745,0.00003835998,0.000007348489,0.000006246919,0.00002186395,0.0001627746,0.9642896,0.001648113,0.00005713107,0.03137072],"study_design_scores_gemma":[0.002003114,0.0008740163,0.07069425,0.0009527935,0.00001238655,0.0000427154,0.00004687892,0.0031645,0.9070576,0.001417959,0.01341294,0.0003208308],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8682743,0.0009252253,0.1265463,0.002977017,0.00006803885,0.0003358574,0.00002236159,0.00003948006,0.0008114035],"genre_scores_gemma":[0.9196511,0.00002640899,0.07871686,0.00005824152,0.00003862482,0.00001220178,0.000002244773,0.000005430531,0.001488883],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06843451,"threshold_uncertainty_score":0.1927572,"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."}}