{"id":"W3212415690","doi":"10.1111/ctr.14534","title":"Characterization and predictive functional profiles on metagenomic 16S rRNA data of liver transplant recipients: A longitudinal study","year":2021,"lang":"en","type":"article","venue":"Clinical Transplantation","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University Health Network","funders":"","keywords":"Metagenomics; Hypervariable region; Microbiome; 16S ribosomal RNA; Biology; Liver transplantation; Ribosomal RNA; Feces; Medicine; Gene; Transplantation; Computational biology; Genetics; Microbiology; Internal medicine","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":[0.001206501,0.0003025318,0.0004829234,0.0006577537,0.0004324812,0.0007176607,0.0001755987,0.0003419518,0.0008317311],"category_scores_gemma":[0.0009925294,0.0001607522,0.0004260084,0.0006091418,0.0001918715,0.0003799982,0.000597102,0.0004820382,0.0003000477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001948798,"about_ca_system_score_gemma":0.0002915162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000547875,"about_ca_topic_score_gemma":0.0009840605,"domain_scores_codex":[0.999606,0.0001008271,0.0000386012,0.0001011856,0.00007433422,0.00007914579],"domain_scores_gemma":[0.9992641,0.00007708998,0.0002864399,0.00008979066,0.0001350178,0.0001476088],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009822749,0.0003272643,0.9398565,0.00005573618,0.0001504076,0.000194572,0.0003486004,0.0001333748,0.0463968,0.00003969731,0.00016729,0.01134766],"study_design_scores_gemma":[0.000006746979,0.0008759087,0.9920574,0.0000196679,0.0001005951,0.0004079411,0.0004029017,0.0006078148,0.004699701,0.00005396824,0.0007545896,0.00001275693],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998623,0.0002205637,0.0005817546,0.00002413422,0.000005109592,0.00001182538,0.0004023387,0.000006454992,0.0001247128],"genre_scores_gemma":[0.9970316,0.0001683841,0.001078683,0.00003645475,0.00001103945,0.00003827182,0.001325315,0.000007732177,0.0003026068],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001206501,"threshold_uncertainty_score":0.006380677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1330403326655124,"score_gpt":0.368368783150241,"score_spread":0.2353284504847285,"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."}}