{"id":"W3028383715","doi":"10.1093/bioinformatics/btaa542","title":"TaxoNN: ensemble of neural networks on stratified microbiome data for disease prediction","year":2020,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":79,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; Princess Margaret Cancer Centre; Hospital for Sick Children; Public Health Ontario; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Crohn's and Colitis Canada; Leona M. and Harry B. Helmsley Charitable Trust","keywords":"Microbiome; Computer science; Artificial intelligence; Machine learning; Convolutional neural network; Artificial neural network; Ensemble learning; Pattern recognition (psychology); Data mining; Bioinformatics; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002913961,0.001725997,0.001169811,0.00130129,0.0004564721,0.0007180349,0.00131671,0.001031031,0.001275753],"category_scores_gemma":[0.004596874,0.0004784279,0.0009857223,0.000920368,0.0002852323,0.001035742,0.001005426,0.001406625,0.0005113571],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009446412,"about_ca_system_score_gemma":0.001106957,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01717769,"about_ca_topic_score_gemma":0.01662789,"domain_scores_codex":[0.9994293,0.0002162086,0.00003844407,0.0001670919,0.00007765338,0.00007119489],"domain_scores_gemma":[0.9985807,0.000677398,0.0001289316,0.0001625841,0.0003608817,0.00008946651],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005874854,0.000259363,0.02629631,0.0001149835,0.0005514182,0.0001721017,0.00006336975,0.7705215,0.002351621,0.0008813529,0.004722091,0.1934784],"study_design_scores_gemma":[0.000006510663,0.00004008371,0.0006020698,0.000007335523,0.00001348093,0.00001163511,0.000004999135,0.9982266,0.0003566275,0.000557239,0.0001685703,0.000004882208],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.391033,0.004063589,0.5859409,0.001341018,0.0005929147,0.0003405615,0.003730748,0.009367837,0.003589499],"genre_scores_gemma":[0.8756751,0.0005748798,0.1163384,0.000338975,0.0001426907,0.000225514,0.004221844,0.0001017862,0.002380789],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01717769,"threshold_uncertainty_score":0.03415543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04297981616172603,"score_gpt":0.2717342480828832,"score_spread":0.2287544319211572,"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."}}