{"id":"W179367881","doi":"","title":"The Southern Alberta Renal Program database: a prototype for patient management and research initiatives.","year":2001,"lang":"en","type":"article","venue":"PubMed","topic":"Dialysis and Renal Disease Management","field":"Medicine","cited_by":107,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Database; Medicine; Comorbidity; Quality assurance; Health care; Computer science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007925057,0.0006950248,0.00107439,0.005827259,0.001117317,0.003308802,0.003575751,0.0007068295,0.03630401],"category_scores_gemma":[0.01632833,0.0009135794,0.0005250013,0.009507615,0.0004170533,0.003151072,0.002658965,0.0008706914,0.01583586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00271284,"about_ca_system_score_gemma":0.01109335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1289775,"about_ca_topic_score_gemma":0.1563889,"domain_scores_codex":[0.9976618,0.0005307113,0.0003893869,0.0002588295,0.000996732,0.0001624801],"domain_scores_gemma":[0.9870867,0.003771196,0.0005695866,0.002214821,0.003890847,0.002466799],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.001442148,0.0002770745,0.01325897,0.0007662355,0.0001408886,0.0003094603,0.0006973451,0.0009328078,0.002131766,0.00546582,0.6659726,0.3086049],"study_design_scores_gemma":[0.001476806,0.0001789287,0.03329384,0.0004326284,0.0002192623,0.0006977004,0.0007978869,0.009032199,0.002774744,0.007753064,0.9431221,0.0002207672],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.03069675,0.004437808,0.1374131,0.009567901,0.0009589756,0.007946515,0.5715839,0.1410843,0.09631078],"genre_scores_gemma":[0.07052612,0.003065411,0.372694,0.001910091,0.0005003295,0.004073879,0.5073169,0.007446585,0.03246668],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1289775,"threshold_uncertainty_score":0.2564536,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05481869280538303,"score_gpt":0.3257786621549846,"score_spread":0.2709599693496015,"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."}}