{"id":"W2340532378","doi":"10.1139/bcb-2016-0022","title":"Divergent evolution for diverse substrate recognition by family 31 glycoside hydrolases","year":2016,"lang":"en","type":"article","venue":"Biochemistry and Cell Biology","topic":"Enzyme Production and Characterization","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Canadian Institutes of Health Research","keywords":"Glycoside hydrolase; Phylogenetic tree; Carbohydrate; Starch; Biochemistry; Enzyme; Biology; Gene; Glycoside; Substrate (aquarium); Substrate specificity; Chemistry; Food science; Botany; Ecology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0005634355,0.0002418145,0.0003983207,0.0007874048,0.0003470583,0.0007936709,0.0003848402,0.0006531043,0.0006425064],"category_scores_gemma":[0.0006236578,0.0002555621,0.0003810025,0.0008082977,0.0005332807,0.0005394791,0.0006233651,0.000722835,0.0005426417],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000408992,"about_ca_system_score_gemma":0.0003203997,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004873101,"about_ca_topic_score_gemma":0.0006170245,"domain_scores_codex":[0.9996986,0.00005386702,0.00002383385,0.00009295323,0.0000736506,0.00005711297],"domain_scores_gemma":[0.9994885,0.0001248985,0.0001214813,0.00008368975,0.0001031026,0.00007836108],"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":[0.000320746,0.00007686013,0.027541,0.00006056294,0.00004183286,0.001266254,0.0005448037,0.0005562754,0.9496121,0.001129364,0.00007618087,0.01877394],"study_design_scores_gemma":[0.00007282072,0.0009244027,0.7011442,0.00009964639,0.0001421964,0.02087089,0.002103109,0.007684217,0.2454442,0.002662548,0.01865548,0.000196211],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969669,0.0006287079,0.001197923,0.00006112641,0.000006845138,0.000008235752,0.0000487352,0.00001690968,0.00106454],"genre_scores_gemma":[0.9956992,0.0006163391,0.002199789,0.00007249718,0.00001236952,0.0000117356,0.0002559813,0.00002213638,0.001110005],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007936709,"threshold_uncertainty_score":0.002979815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01212794153534878,"score_gpt":0.216274610062241,"score_spread":0.2041466685268922,"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."}}