{"id":"W2345377807","doi":"10.1111/hdi.12422","title":"Optimizing dialysate potassium","year":2016,"lang":"en","type":"article","venue":"Hemodialysis International","topic":"Potassium and Related Disorders","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Humber River Regional Hospital","funders":"","keywords":"Medicine; Potassium; Hemodialysis; Hyperkalemia; Internal medicine; Metallurgy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.003104697,0.0002481222,0.0004144567,0.0005165213,0.0007661245,0.001989675,0.000919686,0.0008666157,0.003207459],"category_scores_gemma":[0.006519222,0.00009014232,0.0003589706,0.0004085824,0.0002753408,0.001133861,0.001358852,0.0008868175,0.001094149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001519433,"about_ca_system_score_gemma":0.002972619,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003934873,"about_ca_topic_score_gemma":0.005161019,"domain_scores_codex":[0.9978929,0.0008250606,0.0002903763,0.000178274,0.0005020946,0.0003113145],"domain_scores_gemma":[0.9973971,0.0004700896,0.0005120212,0.0001536081,0.001036252,0.0004311134],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007071789,0.001951815,0.1034396,0.002279771,0.0001829313,0.0009181611,0.00171924,0.004440133,0.01845223,0.008491623,0.09924253,0.7581748],"study_design_scores_gemma":[0.0004332691,0.00272156,0.1722308,0.004055585,0.0005409747,0.005189552,0.005437214,0.0118429,0.05386638,0.02054091,0.7228891,0.0002518697],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"editorial","genre_scores_codex":[0.4535842,0.04558043,0.1551722,0.1456902,0.002316129,0.001901787,0.001437232,0.003939761,0.190378],"genre_scores_gemma":[0.901795,0.008895512,0.06464426,0.01163496,0.0005752833,0.0003446425,0.0004316499,0.0001941562,0.01148458],"genre_candidate":"editorial","genre_consensus":null,"teacher_disagreement_score":0.003934873,"threshold_uncertainty_score":0.01641941,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01295952361299294,"score_gpt":0.2601162858022676,"score_spread":0.2471567621892747,"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."}}