{"id":"W3035106393","doi":"10.1007/s00253-020-10715-8","title":"Identification of a chitosanase from the marine metagenome and its molecular improvement based on evolution data","year":2020,"lang":"en","type":"article","venue":"Applied Microbiology and Biotechnology","topic":"Studies on Chitinases and Chitosanases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Biotechnology Research Institute","funders":"","keywords":"Chitosanase; Metagenomics; Escherichia coli; Mutant; Gene; Biology; Chitosan; Computational biology; Biochemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009086444,0.0001551108,0.0001892516,0.00002685778,0.000093846,0.000006007328,0.0003202108,0.0002543505,0.000007650157],"category_scores_gemma":[0.00007310828,0.0001151932,0.00002720452,0.00008850061,0.0002771466,0.000001736088,0.0006604359,0.0001235937,0.000002373253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003350981,"about_ca_system_score_gemma":0.00002064556,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001902792,"about_ca_topic_score_gemma":0.00004162125,"domain_scores_codex":[0.9989988,0.00003029692,0.0002292249,0.0005567547,0.0000287779,0.000156191],"domain_scores_gemma":[0.9993109,0.00003145446,0.0001394729,0.0004700397,0.00001681085,0.00003139539],"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":[0.000168234,0.00003954142,0.0001705526,0.00001261937,0.000106958,0.000001302979,0.000009009294,0.000007273952,0.9941432,0.001661556,0.0001555286,0.003524168],"study_design_scores_gemma":[0.0006383581,0.0003879989,0.001192928,0.000003186095,0.00007650949,0.000004059569,0.00014402,0.0002558377,0.9946566,0.000119401,0.002391477,0.0001296797],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902673,0.002313724,0.00142126,0.005024045,0.00003813788,0.0002972299,0.0005825805,0.00001784964,0.00003789092],"genre_scores_gemma":[0.996595,0.000434478,0.0001754098,0.001876484,0.000054452,0.00001911497,0.0008327679,0.00001008693,0.000002260016],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006327664,"threshold_uncertainty_score":0.469744,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009144994267455575,"score_gpt":0.2095007913127738,"score_spread":0.2003557970453182,"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."}}