{"id":"W4411436820","doi":"10.1093/bioadv/vbaf140","title":"Prediction of the infecting organism in peritoneal dialysis patients with acute peritonitis using interpretable Tsetlin Machines","year":2024,"lang":"en","type":"article","venue":"Bioinformatics Advances","topic":"Dialysis and Renal Disease Management","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Infection and Immunity","funders":"Engineering and Physical Sciences Research Council; Medical Research Council; National Institute for Health and Care Research","keywords":"Peritoneal dialysis; Peritonitis; Organism; Medicine; Dialysis; Intensive care medicine; Computational biology; Internal medicine; Biology; Genetics","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":[0.001325222,0.00067783,0.0003720708,0.001545157,0.0001991398,0.001200955,0.0004653623,0.0007311385,0.002028626],"category_scores_gemma":[0.008083405,0.0001536076,0.0004702834,0.0007698979,0.0003931968,0.0006231195,0.000703795,0.0006979496,0.0005802543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000497226,"about_ca_system_score_gemma":0.000544973,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001246846,"about_ca_topic_score_gemma":0.001303958,"domain_scores_codex":[0.9994824,0.0002077705,0.00006193392,0.000123325,0.00008075318,0.00004376399],"domain_scores_gemma":[0.9968837,0.002170953,0.0004048272,0.0001610507,0.0002657839,0.0001135278],"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":[0.001952489,0.0003852321,0.3261933,0.0005976891,0.0002593544,0.001310216,0.0004501471,0.3831198,0.009290096,0.005578571,0.02181752,0.2490456],"study_design_scores_gemma":[0.00003416949,0.0001368432,0.01356484,0.00007502524,0.00003780905,0.0003658773,0.0001148508,0.9653446,0.005507224,0.01156044,0.003228013,0.00003027324],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7140981,0.001973081,0.2647927,0.002972755,0.0003369181,0.0002277229,0.007913418,0.003581024,0.004104294],"genre_scores_gemma":[0.9473579,0.0003015837,0.04748429,0.0002296401,0.00008511681,0.00009159759,0.003810488,0.0000552396,0.0005840956],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.002028626,"threshold_uncertainty_score":0.007008493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007110007031997439,"score_gpt":0.2391215279493388,"score_spread":0.2320115209173414,"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."}}