{"id":"W4210793190","doi":"10.1053/j.ajkd.2021.09.023","title":"Biomarkers to Predict CKD After Acute Kidney Injury: News or Noise?","year":2022,"lang":"en","type":"letter","venue":"American Journal of Kidney Diseases","topic":"Acute Kidney Injury Research","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"Academy of Medical Sciences","keywords":"Medicine; Acute kidney injury; Kidney disease; Internal medicine; Intensive care 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01042387,0.001123569,0.002507101,0.001515374,0.003025071,0.005323788,0.002033017,0.0424827,0.007716237],"category_scores_gemma":[0.03905651,0.0006798989,0.001529718,0.001156238,0.002586117,0.006031669,0.001768519,0.03447152,0.007545833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002709613,"about_ca_system_score_gemma":0.003811375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005414406,"about_ca_topic_score_gemma":0.008780577,"domain_scores_codex":[0.994472,0.001874828,0.0009620169,0.0005714906,0.001690893,0.0004287836],"domain_scores_gemma":[0.9689826,0.01851345,0.00151344,0.0007721943,0.006731217,0.003487133],"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":[0.0001788624,0.00008157708,0.001397837,0.00008815272,0.00004030045,0.0005944538,0.00005779762,0.00004392385,0.0001441387,0.002002306,0.9711534,0.02421729],"study_design_scores_gemma":[0.000705343,0.0002332784,0.003390964,0.001366858,0.0001520522,0.001360058,0.0006722197,0.0009046369,0.0002957345,0.01823263,0.9725459,0.0001404372],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0001844784,0.002152472,0.00008637916,0.9716597,0.02448895,0.000007804937,0.00008333163,0.00002138287,0.001315544],"genre_scores_gemma":[0.001955318,0.002598905,0.0004173768,0.8985491,0.09320272,0.00003284097,0.00006902632,0.00002159005,0.00315316],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.0424827,"threshold_uncertainty_score":0.05512732,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01281658363985076,"score_gpt":0.3121971531883055,"score_spread":0.2993805695484547,"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."}}