{"id":"W4308576052","doi":"10.34067/kid.0005562022","title":"A Machine Learning Model to Predict Diuretic Resistance","year":2022,"lang":"en","type":"article","venue":"Kidney360","topic":"Acute Kidney Injury Research","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Seven Oaks General Hospital; University of Manitoba","funders":"","keywords":"Diuretic; Machine learning; Computer science; Artificial intelligence; Intensive care unit; Ensemble learning; Ensemble forecasting; Data mining; Intensive care medicine; Medicine; Internal medicine","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005480814,0.0001840725,0.000308117,0.0002609158,0.0004281294,0.00002402549,0.0003183664,0.00005008272,0.002612437],"category_scores_gemma":[0.001205149,0.0001799022,0.0001072606,0.0006811115,0.00005794219,0.00005922046,0.000489568,0.001060099,0.0002065027],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002694392,"about_ca_system_score_gemma":0.0005891174,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002325429,"about_ca_topic_score_gemma":0.000005444939,"domain_scores_codex":[0.9974488,0.0001448194,0.0002723113,0.0004723711,0.001106665,0.0005550433],"domain_scores_gemma":[0.9983451,0.00006254261,0.00005255771,0.0005494709,0.00009662359,0.0008936633],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001945803,0.0003008081,0.01814122,0.0001581416,0.0001162574,0.0003146686,0.001230638,0.001383034,0.01284426,0.001497879,0.961024,0.00104323],"study_design_scores_gemma":[0.002185567,0.0008354255,0.001017314,0.00005765737,0.00008314275,0.00009797165,0.0001506997,0.09351067,0.0008934438,0.000545922,0.9003398,0.0002823964],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1916085,0.003193583,0.01938926,0.2444561,0.001140908,0.006538399,0.004688871,0.002353639,0.5266308],"genre_scores_gemma":[0.7932937,0.00002691186,0.004529552,0.006797467,0.0001414379,0.0004020023,0.0002668631,0.00008125764,0.1944608],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6016852,"threshold_uncertainty_score":0.9982993,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02712315107756986,"score_gpt":0.3079632175284191,"score_spread":0.2808400664508492,"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."}}