{"id":"W7161766025","doi":"10.82308/11237","title":"Identification and description of latent profiles of patients undergoing maintenance hemodialysis based on hemodynamic indicators","year":2024,"lang":"en","type":"dissertation","venue":"","topic":"Dialysis and Renal Disease Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Hemodialysis; Dialysis; Blood pressure; Cohort; Identification (biology); Hemodynamics; Set (abstract data type); Cluster analysis","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":[0.002538713,0.000374282,0.0005009797,0.001795846,0.0002971769,0.001049733,0.000578774,0.0003987828,0.0009285808],"category_scores_gemma":[0.01203966,0.0001978613,0.0009608343,0.001126993,0.0003164644,0.0006363931,0.0008171296,0.0007306011,0.0001943476],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007470506,"about_ca_system_score_gemma":0.001059721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009688769,"about_ca_topic_score_gemma":0.008697325,"domain_scores_codex":[0.9991002,0.0003342667,0.0001068555,0.0001995044,0.00009769671,0.0001615559],"domain_scores_gemma":[0.9947369,0.002188964,0.001515347,0.000735569,0.0005424527,0.0002808012],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002601645,0.0001072314,0.986388,0.00002136622,0.00009650095,0.00008456032,0.0003511132,0.002932401,0.0006868411,0.0004127517,0.0002909842,0.008368068],"study_design_scores_gemma":[0.00002924246,0.000252128,0.8585623,0.00004307436,0.00009821193,0.0001939806,0.0008046587,0.1365678,0.0006893427,0.002163087,0.0005525454,0.00004347845],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9844668,0.00007323034,0.01349306,0.0001402001,0.000004659478,0.00007295081,0.001535768,0.00003304866,0.0001802065],"genre_scores_gemma":[0.9937212,0.00004161142,0.004049053,0.00001670387,0.000005403404,0.00005113735,0.002024338,0.000005045612,0.00008537482],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009688769,"threshold_uncertainty_score":0.01926476,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007901793160272211,"score_gpt":0.237599361570423,"score_spread":0.2296975684101508,"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."}}