{"id":"W2997236691","doi":"","title":"Why Do I Trust Your Model? Building and Explaining Predictive Models for Peritoneal Dialysis Eligibility","year":2019,"lang":"en","type":"article","venue":"Journal of Computational Vision and Imaging Systems","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Interpretability; Accountability; Peritoneal dialysis; Health care; Transparency (behavior); Computer science; Realm; Medicine; Artificial intelligence; Machine learning; Political science; Law; Computer security; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001370914,0.0001640539,0.0003820035,0.00028772,0.0002246158,0.000685579,0.0003074105,0.00004115906,0.000001325918],"category_scores_gemma":[0.00008965122,0.0001382159,0.00010819,0.0001896142,0.00005507971,0.00212937,0.0001279156,0.0001545086,9.54447e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008037779,"about_ca_system_score_gemma":0.0001093781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002429889,"about_ca_topic_score_gemma":3.052901e-7,"domain_scores_codex":[0.9981454,0.0001056982,0.0006934782,0.0003102584,0.0005219101,0.0002232645],"domain_scores_gemma":[0.9980005,0.0004689407,0.0004587026,0.000162481,0.0007559132,0.000153468],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000584799,0.00003558636,0.001201018,0.00006047076,0.00003318936,0.000003545649,0.002800961,0.9663303,0.0006292322,0.0234052,0.0003219162,0.005120107],"study_design_scores_gemma":[0.0003565847,0.0001568356,0.0002336781,0.0001909642,0.00001558221,0.0001299993,0.001313372,0.9521452,0.00009776488,0.04504649,0.0001753062,0.0001382735],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2432302,0.0007252551,0.7547607,0.0005957295,0.0003647151,0.0002083508,0.000005060371,0.000020309,0.00008963691],"genre_scores_gemma":[0.9466872,0.00002356922,0.05293829,0.0001948838,0.0001206797,0.000005759666,0.00000120244,0.00001120677,0.00001721759],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.703457,"threshold_uncertainty_score":0.6611053,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02535620831293633,"score_gpt":0.3226810353900463,"score_spread":0.2973248270771099,"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."}}