{"id":"W2562791537","doi":"10.1016/j.pbiomolbio.2016.12.002","title":"Automated protein design: Landmarks and operational principles","year":2016,"lang":"en","type":"review","venue":"Progress in Biophysics and Molecular Biology","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Protein design; Folding (DSP implementation); Heuristic; Template; Presentation (obstetrics); Protein folding; Software engineering; Artificial intelligence; Data science; Protein structure; Programming language; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00186801,0.001439344,0.00169939,0.001812175,0.0004470409,0.00226135,0.002904206,0.001495129,0.002381278],"category_scores_gemma":[0.002602544,0.001009262,0.0009121521,0.00373094,0.004068503,0.003678189,0.001966863,0.00257258,0.002051549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001214421,"about_ca_system_score_gemma":0.00171986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001110356,"about_ca_topic_score_gemma":0.0008085623,"domain_scores_codex":[0.9990344,0.0002028973,0.0000966263,0.0002333731,0.0003844147,0.00004826528],"domain_scores_gemma":[0.9987531,0.0007012202,0.0001242149,0.0002043038,0.0001795529,0.00003771417],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005968866,0.00007028081,0.0003241951,0.00577659,0.00009372959,0.00007300107,0.00008485799,0.0166267,0.002574822,0.1806368,0.008740835,0.7849385],"study_design_scores_gemma":[0.00005373635,0.0001858321,0.0005550855,0.002054596,0.00009500569,0.0007635746,0.00007530995,0.03128766,0.005960531,0.4301262,0.528737,0.0001054129],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00190485,0.7116736,0.2750233,0.001585889,0.0005081837,0.00004630391,0.0001777294,0.0004869406,0.008593123],"genre_scores_gemma":[0.03297357,0.7743078,0.1878652,0.0005240107,0.000732049,0.0001339301,0.0004343014,0.0001569587,0.002872248],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002904206,"threshold_uncertainty_score":0.009879112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01695946039893097,"score_gpt":0.319000056366995,"score_spread":0.302040595968064,"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."}}