{"id":"W4394487465","doi":"10.6084/m9.figshare.20701291","title":"Interactions between medications and the gut microbiome in inflammatory bowel disease: meta data","year":2022,"lang":"en","type":"dataset","venue":"Figshare","topic":"Microscopic Colitis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Inflammatory bowel disease; Microbiome; Gut microbiome; Metagenomics; Disease; Medicine; Inflammatory Bowel Diseases; Meta-analysis; Computational biology; Bioinformatics; Immunology; Biology; Internal medicine; Genetics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001853972,0.001278244,0.001701863,0.002571141,0.0005400471,0.001831223,0.001980811,0.001612353,0.08263569],"category_scores_gemma":[0.01599084,0.0006945546,0.004050528,0.004182119,0.000226465,0.0007355543,0.001750799,0.001514047,0.02123075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009403155,"about_ca_system_score_gemma":0.002524045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01419931,"about_ca_topic_score_gemma":0.0286021,"domain_scores_codex":[0.9983156,0.0004329397,0.0003414318,0.0005097567,0.0002469278,0.0001533476],"domain_scores_gemma":[0.9933771,0.004102996,0.0008500706,0.0008180134,0.0005792551,0.0002725711],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001031239,0.00008121984,0.01533722,0.01885936,0.003582642,0.0001308092,0.00007083451,0.001724922,0.0004716254,0.0008401934,0.9467902,0.0110798],"study_design_scores_gemma":[0.00520218,0.000257428,0.0640547,0.008951247,0.006153008,0.0005407422,0.0001859287,0.001954424,0.0009186974,0.003523983,0.9080788,0.0001787435],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002691402,0.0003122977,0.0001054333,0.00008425162,0.00002082081,0.00001851997,0.9988255,0.0001100143,0.0002540738],"genre_scores_gemma":[0.004012496,0.0005232637,0.001162129,0.0002605131,0.00002553246,0.0004462967,0.9924411,0.000107609,0.001021088],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08263569,"threshold_uncertainty_score":0.276444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07748743604615228,"score_gpt":0.3508073671337661,"score_spread":0.2733199310876139,"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."}}