{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003000957,0.0007679431,0.0005327272,0.001099373,0.0002543714,0.0004033564,0.0003846817,0.0004220226,0.001217189],"category_scores_gemma":[0.0003155834,0.0003627602,0.0006787285,0.0005894908,0.0002761676,0.0001591718,0.0003767383,0.0007751904,0.0007640685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002494094,"about_ca_system_score_gemma":0.0002564745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006568356,"about_ca_topic_score_gemma":0.0008561254,"domain_scores_codex":[0.9996766,0.00005182253,0.0000307714,0.00008129388,0.00009129525,0.00006825768],"domain_scores_gemma":[0.9996976,0.00007629414,0.00008042782,0.00003697036,0.00003474399,0.00007392087],"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":[0.00007856343,0.00002787863,0.0001478517,0.00003054475,0.000006375845,0.00003676043,0.0000145771,0.00004323687,0.9984675,0.00003577185,0.00001355877,0.001097205],"study_design_scores_gemma":[0.00008515126,0.0008830941,0.01485275,0.0000257396,0.0001039192,0.0005214436,0.00005063507,0.001386294,0.9779033,0.00009463358,0.004073759,0.00001932023],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.963021,0.001219836,0.02816583,0.0002302903,0.00005481578,0.0004838027,0.004560427,0.0002919717,0.001972186],"genre_scores_gemma":[0.9073384,0.003413826,0.05263247,0.0003088229,0.00005892226,0.0008237056,0.02239076,0.0003299604,0.01270309],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001217189,"threshold_uncertainty_score":0.004071891,"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."}}