{"id":"W2944662319","doi":"10.14740/jocmr3791","title":"Characteristics of Gut Microbiota in Patients With Diabetes Determined by Data Mining Analysis of Terminal Restriction Fragment Length Polymorphisms","year":2019,"lang":"en","type":"article","venue":"Journal of Clinical Medicine Research","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Terminal restriction fragment length polymorphism; Medicine; Terminal (telecommunication); Restriction fragment length polymorphism; Gut flora; Fragment (logic); Restriction fragment; Genetics; Computational biology; Bioinformatics; Gene; Biology; Immunology; Genotype; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.001113712,0.0003189222,0.0005012223,0.001232113,0.0002511001,0.0005881932,0.0001823539,0.0004018333,0.0002954604],"category_scores_gemma":[0.002481501,0.0001369115,0.0004844412,0.001081533,0.0001512221,0.0002242016,0.0002720931,0.0002967969,0.00009626558],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001470197,"about_ca_system_score_gemma":0.0001938027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008084109,"about_ca_topic_score_gemma":0.0009624977,"domain_scores_codex":[0.999368,0.0001956305,0.0001135081,0.0001563256,0.000105411,0.00006111064],"domain_scores_gemma":[0.9983644,0.0006204561,0.0005922583,0.00008944671,0.0002235425,0.0001099977],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002313769,0.00005500098,0.9906912,0.00002627124,0.00006854258,0.00008155025,0.00007211384,0.0001879616,0.002477112,0.000006866856,0.00004936005,0.006052549],"study_design_scores_gemma":[0.0000229643,0.0003881105,0.9897743,0.00002395477,0.0001364658,0.001028313,0.0004098097,0.005651643,0.002168242,0.00009023305,0.0002945986,0.0000112361],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983006,0.0002056495,0.001098082,0.00003227808,0.000004350075,0.00001415946,0.000251436,0.000006229133,0.00008710504],"genre_scores_gemma":[0.9968809,0.0001015335,0.002524601,0.00002329319,0.0000072882,0.00001900002,0.0003995234,0.000002072522,0.00004185279],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001232113,"threshold_uncertainty_score":0.005889952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06441271475365429,"score_gpt":0.4244770343066238,"score_spread":0.3600643195529695,"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."}}