{"id":"W2769749548","doi":"10.1021/acschembio.7b00996","title":"Determinants and Prediction of Esterase Substrate Promiscuity Patterns","year":2017,"lang":"en","type":"article","venue":"ACS Chemical Biology","topic":"Enzyme Catalysis and Immobilization","field":"Biochemistry, Genetics and Molecular Biology","cited_by":147,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"H2020 Societal Challenges; Biotechnology and Biological Sciences Research Council; Natural Sciences and Engineering Research Council of Canada; Ministerio de Economía y Competitividad; Genome Canada; European Regional Development Fund; Deutsche Forschungsgemeinschaft; FP7 Food, Agriculture and Fisheries, Biotechnology; Departamento Administrativo de Ciencia, Tecnología e Innovación (COLCIENCIAS)","keywords":"Substrate (aquarium); Active site; Sasa; Catalytic triad; Dehalogenase; Computational biology; Biology; Chemistry; Biological system; Enzyme; Biochemistry; Ecology","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":[0.00008102036,0.00007894095,0.0001231482,0.00001091326,0.00005262834,0.0000122266,0.0001397213,0.0001620237,0.000004845117],"category_scores_gemma":[0.0001415514,0.00006586098,0.00003133713,0.000009059514,0.0001598553,0.000005221131,0.0001219703,0.00003926806,8.308654e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002823223,"about_ca_system_score_gemma":0.00001180936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001364367,"about_ca_topic_score_gemma":0.0000104318,"domain_scores_codex":[0.9994602,0.00001796499,0.0001572887,0.0002306613,0.00002597634,0.0001078824],"domain_scores_gemma":[0.9994377,0.00000607422,0.0001329987,0.0003385693,0.00004542603,0.00003920231],"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":[0.00001953634,0.00001991804,0.2817909,0.0000131943,0.000009348591,2.60518e-7,0.000006504681,5.616917e-8,0.7163185,0.00001190371,0.00001936983,0.001790446],"study_design_scores_gemma":[0.0003041895,0.0001015422,0.09068854,0.000008217676,0.0000131836,0.000006553109,0.000005049899,0.00001692521,0.908463,0.00005338343,0.0002829272,0.00005647036],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994888,0.00009372471,0.00009665996,0.00002545522,0.00005098441,0.00007576553,0.00007452648,0.000003653012,0.00009040653],"genre_scores_gemma":[0.9993622,0.0001553455,0.00004045688,0.00002646023,0.00007397914,0.000009993472,0.0002855431,0.000005859592,0.00004010332],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1921445,"threshold_uncertainty_score":0.2685733,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01538168366789507,"score_gpt":0.2714896223396223,"score_spread":0.2561079386717272,"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."}}