{"id":"W4318261797","doi":"10.2215/cjn.0000000000000089","title":"Artificial Intelligence and Machine Learning in Dialysis","year":2023,"lang":"en","type":"article","venue":"Clinical Journal of the American Society of Nephrology","topic":"Dialysis and Renal Disease Management","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Diabetes and Digestive and Kidney Diseases","keywords":"Artificial intelligence; Machine learning; Dialysis; Medical prescription; Process (computing); Field (mathematics); Medicine; Health care; Computer science; Unsupervised learning; Data science; Mathematics; Surgery","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003798689,0.0005750218,0.0008980039,0.001436946,0.000898455,0.003450209,0.001210196,0.004534118,0.004938442],"category_scores_gemma":[0.009733558,0.0002938801,0.0005386236,0.002165796,0.006089513,0.005344695,0.002040743,0.005998857,0.0015344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002631222,"about_ca_system_score_gemma":0.0017613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003070965,"about_ca_topic_score_gemma":0.001425578,"domain_scores_codex":[0.997501,0.001412013,0.0001295704,0.0003527993,0.0004940137,0.0001106901],"domain_scores_gemma":[0.9944726,0.004499124,0.0002127005,0.0002276978,0.0004098846,0.0001780565],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004139114,0.00006279718,0.001582251,0.0006147382,0.00005468791,0.0001591303,0.0003477162,0.008761999,0.0001042944,0.7840021,0.05476956,0.1494993],"study_design_scores_gemma":[0.00001243684,0.00002717934,0.0009504291,0.0004550321,0.00000794431,0.0001379006,0.0001536223,0.00784637,0.00009621277,0.8643612,0.1259189,0.00003276745],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.005147606,0.6131407,0.08731873,0.1968111,0.006528233,0.00007423127,0.0003019682,0.0002292036,0.09044821],"genre_scores_gemma":[0.3229039,0.4881784,0.08323851,0.03315809,0.02784294,0.0003828758,0.0006017701,0.0002094211,0.04348413],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004938442,"threshold_uncertainty_score":0.02008963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0809698482615674,"score_gpt":0.3753919727393495,"score_spread":0.2944221244777821,"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."}}