{"id":"W2093389098","doi":"10.1128/aem.71.5.2347-2354.2005","title":"Construction, Analysis, and β-Glucanase Screening of a Bacterial Artificial Chromosome Library from the Large-Bowel Microbiota of Mice","year":2005,"lang":"en","type":"article","venue":"Applied and Environmental Microbiology","topic":"Probiotics and Fermented Foods","field":"Agricultural and Biological Sciences","cited_by":78,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"University of Otago","keywords":"Bacterial artificial chromosome; Biology; Genomic library; Genetics; Escherichia coli; Insert (composites); genomic DNA; Open reading frame; Metagenomics; Gene; clone (Java method); Library; Chromosome; Glucanase; Microbiology; Molecular biology; 16S ribosomal RNA; Peptide sequence; Genome","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":[0.000061134,0.000119916,0.0002279393,0.00001414159,0.0001077987,0.00001356877,0.0001139673,0.0001118463,0.0005153996],"category_scores_gemma":[0.000001143806,0.00005233322,0.00005809861,0.0001011407,0.000407323,0.00004098478,0.0001679836,0.00007710393,0.000002176679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004787302,"about_ca_system_score_gemma":0.000002528133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008264657,"about_ca_topic_score_gemma":0.0001079561,"domain_scores_codex":[0.9992802,0.00003531225,0.0002527241,0.0002436928,0.00002430697,0.000163777],"domain_scores_gemma":[0.9996939,0.00007572715,0.0001335235,0.00005437239,0.000001823635,0.00004061322],"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":[0.00006526628,0.00007179652,0.00861411,0.000001892404,0.0001432347,2.145009e-7,0.00008002035,0.000002514281,0.9800789,0.0001859764,0.00004172375,0.01071438],"study_design_scores_gemma":[0.0008259505,0.0002348062,0.212688,0.0000158055,0.0004198984,0.00002812271,0.001803049,0.00008111804,0.7640151,0.000281999,0.01923492,0.0003712147],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968276,0.0003916858,0.000016227,0.0003704523,0.00002884693,0.0001199901,0.002194489,0.000006956381,0.00004372094],"genre_scores_gemma":[0.9973795,0.0002143558,0.0007083691,0.0001758314,0.0001153264,0.000002289099,0.001396067,0.00000125951,0.000007004702],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2160637,"threshold_uncertainty_score":0.5643264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004377441935599774,"score_gpt":0.1532780465199779,"score_spread":0.1489006045843781,"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."}}