{"id":"W4380190507","doi":"10.1007/978-3-031-34619-4_10","title":"PreCKD_ML: Machine Learning Based Development of Prediction Model for Chronic Kidney Disease and Identify Significant Risk Factors","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Kidney disease; Medicine; Disease; Machine learning; Artificial intelligence; Intensive care medicine; Internal medicine; Computer science","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":[0.0007722603,0.0007101403,0.0006515566,0.0007280917,0.0002991853,0.000877891,0.0011014,0.0006403963,0.01211325],"category_scores_gemma":[0.002282067,0.0004132933,0.0009111714,0.0005348832,0.00009930431,0.0007625994,0.0007160443,0.001116479,0.005702994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003043158,"about_ca_system_score_gemma":0.0009093281,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005621174,"about_ca_topic_score_gemma":0.006301267,"domain_scores_codex":[0.9997634,0.00004489985,0.00001852999,0.00007443794,0.00007671952,0.00002205958],"domain_scores_gemma":[0.9994774,0.0003081333,0.00002020216,0.00004826298,0.0001263077,0.00001963199],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003702371,0.000314311,0.01125855,0.0003080389,0.0002659623,0.0003027818,0.00006240737,0.1018301,0.004145663,0.003832521,0.1176223,0.7596872],"study_design_scores_gemma":[0.00005450638,0.00009315046,0.003253116,0.00004188542,0.00007875283,0.0002535499,0.00002207535,0.963618,0.006170999,0.005627572,0.02075557,0.00003080125],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03168412,0.001948128,0.8975719,0.001483435,0.000657774,0.0002428943,0.01804512,0.0408317,0.007534921],"genre_scores_gemma":[0.2478033,0.001643912,0.6800481,0.0007011691,0.0004901807,0.0006088439,0.03989439,0.001734729,0.02707538],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01211325,"threshold_uncertainty_score":0.04052281,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.092521679932356,"score_gpt":0.3543387385905006,"score_spread":0.2618170586581446,"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."}}