{"id":"W2772789328","doi":"10.24870/cjb.2017-a254","title":"Next Generation sequencing as a tool in gut microbiota to discriminate between wellness and obese","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Biotechnology","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Gut flora; Biology; Gut microbiome; Computational biology; Immunology","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":[0.001761351,0.0003448384,0.0005530224,0.001990415,0.0003351328,0.0008008925,0.0002604406,0.000536203,0.001491213],"category_scores_gemma":[0.001747631,0.0002319322,0.0004553967,0.001155574,0.0001876818,0.000348289,0.0004768451,0.0006681609,0.000560434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002221385,"about_ca_system_score_gemma":0.0003352392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009718766,"about_ca_topic_score_gemma":0.002008349,"domain_scores_codex":[0.9990065,0.0004637084,0.00006555918,0.0001839487,0.0002270702,0.00005336948],"domain_scores_gemma":[0.9994364,0.0002203934,0.0001179465,0.00004884996,0.0001277631,0.00004867143],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001347204,0.0005127226,0.1390057,0.001448106,0.0005888617,0.0008205157,0.0009969604,0.002606656,0.6285285,0.001565111,0.004663633,0.2179162],"study_design_scores_gemma":[0.0001965175,0.003170679,0.6449037,0.001038302,0.000935656,0.003447092,0.002021674,0.06860738,0.205378,0.006910226,0.06314597,0.0002448262],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7616868,0.02095423,0.1924254,0.001706541,0.0006760109,0.0008348165,0.01172331,0.001886218,0.008106763],"genre_scores_gemma":[0.6034483,0.006122363,0.3775181,0.001335623,0.0001582667,0.001013545,0.005878144,0.0002005376,0.004325134],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001990415,"threshold_uncertainty_score":0.009315014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03950111368439862,"score_gpt":0.2751685584369847,"score_spread":0.2356674447525861,"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."}}