{"id":"W2791942296","doi":"10.1128/mbio.00630-18","title":"Leveraging Existing 16S rRNA Gene Surveys To Identify Reproducible Biomarkers in Individuals with Colorectal Tumors","year":2018,"lang":"en","type":"review","venue":"mBio","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institute of Diabetes and Digestive and Kidney Diseases; Government of Canada; National Institutes of Health; National Cancer Institute; Canadian Institutes of Health Research","keywords":"Taxon; Biology; Odds ratio; Colorectal cancer; Feces; Adenoma; 16S ribosomal RNA; Disease; Cancer; Pathology; Internal medicine; Bioinformatics; Medicine; Gene; Genetics; Ecology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006871926,0.0006943343,0.0008014175,0.00193864,0.000439726,0.001087649,0.0004434775,0.0007625634,0.0006703837],"category_scores_gemma":[0.01365704,0.0003786687,0.0009079705,0.00200935,0.0003374766,0.0006446114,0.0006513132,0.0005742972,0.0003010247],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002503013,"about_ca_system_score_gemma":0.0004473926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001920552,"about_ca_topic_score_gemma":0.004469506,"domain_scores_codex":[0.9961971,0.001744718,0.0003885115,0.0008720597,0.0006096402,0.0001878875],"domain_scores_gemma":[0.9907655,0.003716187,0.003261102,0.0007979264,0.001200265,0.000259067],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0002791728,0.00005412606,0.9734955,0.0001695937,0.0005258141,0.00004851144,0.0001044878,0.001141052,0.007225133,0.00004684121,0.0002449424,0.01666478],"study_design_scores_gemma":[0.0000333222,0.00101505,0.9762477,0.0002016966,0.000834993,0.0003995963,0.0003948043,0.009886071,0.007381352,0.0007966395,0.002755743,0.00005309244],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"review","genre_scores_codex":[0.9711586,0.005452622,0.0194674,0.0002765942,0.00008454438,0.0001246005,0.002398349,0.00009871841,0.0009386307],"genre_scores_gemma":[0.9869602,0.0005856164,0.01110422,0.000158663,0.00005568687,0.00006665431,0.0008749574,0.00001802922,0.0001760054],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.006871926,"threshold_uncertainty_score":0.03634262,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0699464527790222,"score_gpt":0.3712723396422376,"score_spread":0.3013258868632154,"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."}}