{"id":"W2761379268","doi":"10.1186/s12859-017-1843-1","title":"Interpretation of microbiota-based diagnostics by explaining individual classifier decisions","year":2017,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research","funders":"National Science Council; Vrije Universiteit Amsterdam; ZonMw","keywords":"Classifier (UML); Machine learning; Artificial intelligence; Gut flora; Computer science; Biology; Immunology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00535468,0.001540778,0.0008004748,0.001861819,0.0005617582,0.002405161,0.001294325,0.001913201,0.0022274],"category_scores_gemma":[0.02220141,0.0003421763,0.001432631,0.0005615143,0.001006943,0.001157821,0.001061082,0.001592112,0.000495141],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001297853,"about_ca_system_score_gemma":0.001341106,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002029631,"about_ca_topic_score_gemma":0.001561099,"domain_scores_codex":[0.9967487,0.001270262,0.0002712644,0.0008867272,0.0006398163,0.0001831592],"domain_scores_gemma":[0.9872463,0.009196688,0.001098183,0.001022288,0.001226429,0.0002101045],"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":[0.00147165,0.00034787,0.1006066,0.0008211877,0.000677498,0.00145073,0.001645266,0.4268875,0.0286868,0.02082924,0.006028399,0.4105473],"study_design_scores_gemma":[0.00003900057,0.0001310664,0.005585551,0.00009463352,0.0001193852,0.0002676877,0.0001263346,0.9482968,0.009209777,0.03329739,0.002783497,0.00004889109],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1158969,0.000769021,0.8775586,0.00141812,0.0001613938,0.0001862936,0.000769335,0.001631554,0.001608753],"genre_scores_gemma":[0.7013895,0.0002548097,0.2958747,0.0003433542,0.0001223064,0.0001876314,0.0009364076,0.0001652938,0.0007259702],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00535468,"threshold_uncertainty_score":0.02831858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0311724263482281,"score_gpt":0.2971729783402441,"score_spread":0.266000551992016,"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."}}