{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009341119,0.0007154983,0.0006249213,0.001127023,0.0006328941,0.003148934,0.001585084,0.001585287,0.00259935],"category_scores_gemma":[0.06832444,0.0004920686,0.001125514,0.0007916842,0.00189222,0.004570394,0.001797176,0.003456095,0.0003747476],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001662292,"about_ca_system_score_gemma":0.001640791,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008403356,"about_ca_topic_score_gemma":0.007754829,"domain_scores_codex":[0.9961844,0.002551654,0.0001721469,0.0005135816,0.0003843092,0.0001938621],"domain_scores_gemma":[0.950636,0.04123636,0.00331942,0.002648222,0.001761801,0.0003982433],"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":[0.0005480425,0.000288114,0.07492587,0.0005543103,0.0006489987,0.001002469,0.00778415,0.4145458,0.002254764,0.347345,0.01630403,0.1337985],"study_design_scores_gemma":[0.00004319418,0.00004517655,0.004212121,0.0001593576,0.0001049946,0.0001318955,0.0005443523,0.7496071,0.0008099188,0.240031,0.004257874,0.00005303403],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1355364,0.0006561549,0.8270659,0.03018513,0.0002020614,0.0001229558,0.0008679995,0.0007537899,0.004609452],"genre_scores_gemma":[0.8938115,0.0003613924,0.1032555,0.00103357,0.0001163324,0.00009597356,0.0004513421,0.0001212967,0.0007529565],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009341119,"threshold_uncertainty_score":0.04940116,"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."}}