{"id":"W2778950119","doi":"10.3168/jds.2017-13356","title":"Symposium review: Mining metagenomic and metatranscriptomic data for clues about microbial metabolic functions in ruminants","year":2017,"lang":"en","type":"review","venue":"Journal of Dairy Science","topic":"Ruminant Nutrition and Digestive Physiology","field":"Agricultural and Biological Sciences","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Livestock and Meat Agency; Alberta Innovates; Alberta Innovates - Technology Futures","keywords":"Metagenomics; Rumen; Microbiome; Biology; Computational biology; Genome; Microorganism; Transcriptome; Biotechnology; Fermentation; Bacteria; Gene; Bioinformatics; Genetics; Food science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001721034,0.001271037,0.002369203,0.006165605,0.0004007568,0.002471021,0.001136834,0.00169789,0.004516725],"category_scores_gemma":[0.003409078,0.0004253525,0.001577996,0.007063942,0.0004740247,0.00238464,0.001006797,0.0014499,0.002572485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008160216,"about_ca_system_score_gemma":0.0035087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001355385,"about_ca_topic_score_gemma":0.002037783,"domain_scores_codex":[0.9991405,0.0001705333,0.0001956604,0.0001789005,0.0002545915,0.00005964466],"domain_scores_gemma":[0.9969381,0.0009358084,0.000586251,0.00007609603,0.00121394,0.0002497798],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002115276,0.00007695995,0.0013044,0.1128053,0.000989776,0.0004927859,0.0002423012,0.0004690063,0.005047141,0.001426052,0.1483883,0.7285464],"study_design_scores_gemma":[0.00002215788,0.0001316026,0.003282843,0.01596487,0.0008845132,0.001095328,0.0001964683,0.0001495137,0.000968829,0.0008453943,0.9763919,0.00006670788],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0002354538,0.995669,0.000361906,0.001145548,0.001860131,0.00002254687,0.000158464,0.0000274689,0.0005194813],"genre_scores_gemma":[0.0008183621,0.9953794,0.0006710834,0.0008270534,0.001472988,0.00002207127,0.0002853127,0.000008532507,0.0005151552],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.006165605,"threshold_uncertainty_score":0.01510996,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.143195070300205,"score_gpt":0.3651094278443601,"score_spread":0.2219143575441551,"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."}}