{"id":"W3028270276","doi":"10.1038/s41396-020-0678-3","title":"Linking perturbations to temporal changes in diversity, stability, and compositions of neonatal calf gut microbiota: prediction of diarrhea","year":2020,"lang":"en","type":"article","venue":"The ISME Journal","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":158,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; University of Alberta","funders":"Agricultural Science and Technology Innovation Program; Natural Sciences and Engineering Research Council of Canada; Dairy Farmers of Manitoba; Chinese Academy of Agricultural Sciences; University of Washington","keywords":"Biology; Gut flora; Diarrhea; Lachnospiraceae; Antimicrobial; Ruminococcus; Microbiology; Microbiome; Antimicrobial peptides; Immunology; Bacteria; Firmicutes; Internal medicine; Bioinformatics; Medicine","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":[0.0005508878,0.0003502871,0.0004494452,0.000809108,0.0001684716,0.0005711415,0.0001740824,0.0004226803,0.0003480345],"category_scores_gemma":[0.001154794,0.0001338226,0.0002605273,0.0005664175,0.0001319088,0.0002894461,0.0003189782,0.0003567706,0.0001047575],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002629318,"about_ca_system_score_gemma":0.0002662242,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003895984,"about_ca_topic_score_gemma":0.005908808,"domain_scores_codex":[0.9996275,0.00007115918,0.00002904396,0.0001130794,0.00008415138,0.00007510389],"domain_scores_gemma":[0.9992939,0.0001888912,0.0002467918,0.00003574016,0.0001314267,0.000103195],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006220134,0.0001008357,0.8307968,0.0001589049,0.0001484752,0.0001952142,0.0001356151,0.001901655,0.1439912,0.00003722916,0.0001205624,0.02179151],"study_design_scores_gemma":[0.00000313027,0.0003414593,0.9810929,0.00001889985,0.00006761104,0.0001933024,0.000196143,0.007965927,0.009738756,0.00005729932,0.0003105887,0.00001400771],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964817,0.0007315881,0.002130021,0.00001710001,0.000006969361,0.00001023262,0.0004211314,0.0000149208,0.0001863692],"genre_scores_gemma":[0.9973509,0.0003025438,0.001640507,0.00001951793,0.000003838935,0.00001043529,0.000543969,0.000003189657,0.0001251622],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003895984,"threshold_uncertainty_score":0.007746637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02733295253647221,"score_gpt":0.2465526020997127,"score_spread":0.2192196495632405,"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."}}