{"id":"W3214361435","doi":"10.1093/bioinformatics/btab754","title":"Mian: interactive web-based microbiome data table visualization and machine learning platform","year":2021,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Context (archaeology); Categorical variable; Source code; Visualization; Machine learning; Metadata; Data mining; Artificial intelligence; MIT License; Table (database); License; Information retrieval; World Wide Web; Programming language","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000152754,0.000124214,0.0001257637,0.00004673388,0.000126335,0.00007208357,0.0001415508,0.0001160209,0.00003783649],"category_scores_gemma":[0.0000919767,0.0001204805,0.0000209731,0.0001216283,0.00003759153,0.00002528159,0.0002761484,0.0001031021,0.00001891012],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001758574,"about_ca_system_score_gemma":0.0002463016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001449694,"about_ca_topic_score_gemma":0.00007276811,"domain_scores_codex":[0.9992909,0.00002179021,0.0002485385,0.0001809564,0.00006046021,0.0001973591],"domain_scores_gemma":[0.9993551,0.00001335846,0.0001223937,0.0003463949,0.00009239384,0.00007034202],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009474975,0.0001138901,0.002863074,0.0004940616,0.00008054938,0.000006071785,0.0004161651,0.00006651726,0.9745411,0.0001194612,0.01678445,0.004419875],"study_design_scores_gemma":[0.00178348,0.0002181613,0.0005454295,0.00008648814,0.0000372628,0.0001068577,0.0006540922,0.127629,0.1863711,0.000005451572,0.6822077,0.0003550369],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9373271,0.003824938,0.05084407,0.0006714515,0.0006321625,0.0006304726,0.001466526,0.0001175673,0.004485637],"genre_scores_gemma":[0.9412975,0.00130466,0.02212807,0.002555518,0.0001829033,0.000006928713,0.02999336,0.00005346612,0.002477649],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.78817,"threshold_uncertainty_score":0.4913052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02466236800343932,"score_gpt":0.2864016975794296,"score_spread":0.2617393295759903,"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."}}