{"id":"W2789374580","doi":"10.1007/s00134-018-5126-8","title":"Biomarkers for prediction of renal replacement therapy in acute kidney injury: a systematic review and meta-analysis","year":2018,"lang":"en","type":"review","venue":"Intensive Care Medicine","topic":"Acute Kidney Injury Research","field":"Medicine","cited_by":190,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Astute Medical; Grifols; CSL Behring","keywords":"Medicine; Renal replacement therapy; Cystatin C; Acute kidney injury; Biomarker; Internal medicine; Meta-analysis; Area under the curve; Systematic review; Intensive care medicine; Creatinine; Urology; MEDLINE","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":["metaresearch","metaepi_narrow","metaepi_broad"],"consensus_categories":[],"category_scores_codex":[0.002437307,0.0008169329,0.01623963,0.001915067,0.00004985815,0.000009721398,0.0003441687,0.0004053485,0.0005050699],"category_scores_gemma":[0.01285551,0.0004445303,0.002536781,0.002224219,0.0006002053,0.00005867836,0.0001330033,0.0005049242,0.000007029393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004724892,"about_ca_system_score_gemma":0.0007261855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000590264,"about_ca_topic_score_gemma":0.000003068702,"domain_scores_codex":[0.9938968,0.0006931745,0.00290946,0.001036176,0.0009985584,0.0004658654],"domain_scores_gemma":[0.9880415,0.0005116865,0.001517151,0.001549454,0.007838355,0.0005419046],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.0002836259,0.00001894349,0.000004339854,0.5759561,0.2541682,0.00002395368,0.0002862708,6.9275e-10,0.000004417562,0.000002456967,0.168318,0.000933599],"study_design_scores_gemma":[0.001152702,0.003594949,8.780351e-7,0.1901497,0.667379,0.0001234729,0.0004146029,0.000003983208,0.000009175139,0.000002797136,0.1369884,0.0001802986],"study_design_candidate":"meta_analysis","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[7.589897e-7,0.9706916,0.0001207096,0.004579215,0.0001379511,0.01598319,0.008344909,0.00003304025,0.0001085836],"genre_scores_gemma":[0.000006787918,0.9806639,0.0001505839,0.008070328,0.000128284,0.004540664,0.005539589,0.00008947123,0.0008104228],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.4132108,"threshold_uncertainty_score":0.9998006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.127249217529419,"score_gpt":0.4358425389928024,"score_spread":0.3085933214633834,"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."}}