{"id":"W2977194317","doi":"10.1109/icdim.2018.8847123","title":"On the Analysis of a Public Dataset for Diabetes","year":2018,"lang":"en","type":"article","venue":"","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Visualization; Computer science; Data visualization; Diabetes mellitus; Data science; Software; Information visualization; Medical information; Data mining; Information retrieval; Medicine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007010985,0.00004505476,0.0001001063,0.0001450584,0.0000932986,0.0000537619,0.0008229702,0.00001741039,0.0001688063],"category_scores_gemma":[0.0005600288,0.00002541077,0.0000486016,0.0008529589,0.00004523866,0.00008253026,0.000132594,0.00004597493,0.00001830456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007381697,"about_ca_system_score_gemma":0.00002389362,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006138961,"about_ca_topic_score_gemma":0.0001426969,"domain_scores_codex":[0.9993261,0.00009513951,0.0001156494,0.0001743583,0.0001356377,0.0001531588],"domain_scores_gemma":[0.9981917,0.0008332386,0.00006241418,0.0007776666,0.00009971023,0.00003531644],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001921308,0.0000440453,0.03502084,0.00002019456,0.0002965753,1.068538e-7,0.000292878,0.00006688144,0.00004306513,0.847385,0.09154873,0.02527977],"study_design_scores_gemma":[0.00005859656,0.0002046279,0.0226497,0.000003303561,0.00003510615,5.438124e-8,0.000009124864,0.9406575,0.0003568794,0.003497803,0.03246291,0.00006440287],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2648615,0.00002485403,0.6531534,0.07769479,0.0002642454,0.0004682805,0.0007353855,0.0001323249,0.002665286],"genre_scores_gemma":[0.9868662,2.834679e-7,0.009695871,0.003197752,0.0000276823,0.00001741469,0.0001179817,0.000002307982,0.00007455789],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9405906,"threshold_uncertainty_score":0.184831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06357036794676034,"score_gpt":0.3437222890072336,"score_spread":0.2801519210604732,"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."}}