{"id":"W2276625880","doi":"10.1186/s40697-016-0103-z","title":"Acute Kidney Injury in the Era of Big Data: The 15 <sup>th</sup> Consensus Conference of the Acute Dialysis Quality Initiative (ADQI)","year":2016,"lang":"en","type":"article","venue":"Canadian Journal of Kidney Health and Disease","topic":"Acute Kidney Injury Research","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Medicine; Acute kidney injury; Consensus conference; Intensive care medicine; Dialysis; Kidney disease; Emergency medicine; Nephrology; Medical emergency; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.002754204,0.000236405,0.0007254609,0.0002818957,0.0002876639,0.00004158164,0.001063118,0.00009263596,0.0001521334],"category_scores_gemma":[0.05303356,0.000103911,0.0001909021,0.0006695614,0.001368118,0.000176381,0.0001285599,0.00077448,0.000003490304],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002100762,"about_ca_system_score_gemma":0.1290618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004652168,"about_ca_topic_score_gemma":0.000746586,"domain_scores_codex":[0.9956796,0.001450652,0.001164881,0.000292069,0.0007682069,0.0006445554],"domain_scores_gemma":[0.9472848,0.001560249,0.002149208,0.00326684,0.001889207,0.04384968],"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":[0.002048141,0.0001106997,0.08756346,0.0002968919,0.0004786736,0.0002061451,0.003676015,1.397611e-7,0.000140786,0.0005275584,0.8985208,0.006430698],"study_design_scores_gemma":[0.03730347,0.005747512,0.2792005,0.01131803,0.005819596,0.001225773,0.01748008,0.0006015695,0.001047938,0.01107697,0.6275712,0.0016074],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1830896,0.0007894217,0.00005543169,0.7783197,0.0003095043,0.0009214594,0.03604438,0.000003850702,0.0004667109],"genre_scores_gemma":[0.8887195,0.001027361,0.00005201309,0.1096805,0.0002568488,0.00001339206,0.0001165765,0.00001868197,0.0001151128],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7056299,"threshold_uncertainty_score":0.9549431,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.109025860734157,"score_gpt":0.374192938681616,"score_spread":0.265167077947459,"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."}}