{"id":"W4319333499","doi":"10.1016/j.dib.2023.108921","title":"A synthetic dataset of liver disorder patients","year":2023,"lang":"en","type":"article","venue":"Data in Brief","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Bayesian network; Scripting language; Casual; Data set; Set (abstract data type); Artificial intelligence; Machine learning; Population; Synthetic data; Patient data; Data mining; Medicine; Database","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":[0.001782764,0.0005315061,0.0004143744,0.0006786848,0.0003145069,0.0005857088,0.001091433,0.001284525,0.0042616],"category_scores_gemma":[0.007363971,0.0001984707,0.0006871668,0.0008178576,0.0004583111,0.0003012924,0.0006599042,0.0008799189,0.001047451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007406108,"about_ca_system_score_gemma":0.0009139529,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005138251,"about_ca_topic_score_gemma":0.00529675,"domain_scores_codex":[0.9991282,0.0004501471,0.00006032593,0.0001468868,0.0001307311,0.00008373126],"domain_scores_gemma":[0.9967288,0.001813973,0.0001653584,0.0005238531,0.0005015071,0.0002665146],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.005500351,0.003575602,0.1575707,0.00144739,0.0007534241,0.003825087,0.000691925,0.4155203,0.004954406,0.01055844,0.3097838,0.08581863],"study_design_scores_gemma":[0.002580244,0.002951007,0.139093,0.000457358,0.0003324074,0.00555516,0.001562172,0.6786084,0.009486548,0.024264,0.1348553,0.0002543295],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.7322204,0.001252141,0.02852199,0.004719389,0.0009312794,0.001088433,0.2217985,0.001379948,0.008087895],"genre_scores_gemma":[0.720491,0.0004238911,0.02059344,0.001179051,0.0001787451,0.0007347121,0.2537543,0.0000696148,0.002575343],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.005138251,"threshold_uncertainty_score":0.01425654,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03964919403901191,"score_gpt":0.3172690331896421,"score_spread":0.2776198391506302,"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."}}