{"id":"W2904165123","doi":"10.2196/12528","title":"A Digital Modality Decision Program for Patients With Advanced Chronic Kidney Disease","year":2018,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Dialysis and Renal Disease Management","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of California, San Francisco","keywords":"Modality (human–computer interaction); Kidney disease; Medicine; Disease; Intensive care medicine; Computer science; Medical physics; Internal medicine; Artificial intelligence","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":[0.0005477758,0.0002600101,0.0001517084,0.000295313,0.0004156491,0.0002909509,0.0003267565,0.0002856541,0.009003722],"category_scores_gemma":[0.00217889,0.00007770399,0.000270408,0.0001744107,0.0001581945,0.0004069626,0.0008526288,0.0005383195,0.0005322975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002594529,"about_ca_system_score_gemma":0.0008377587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008457449,"about_ca_topic_score_gemma":0.001935415,"domain_scores_codex":[0.9997922,0.00008441185,0.00001642195,0.00002873591,0.00003156046,0.00004663328],"domain_scores_gemma":[0.9990483,0.0003173914,0.0001309038,0.00002891673,0.0000278376,0.0004465981],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002798648,0.08243647,0.1480579,0.000645101,0.0001066275,0.0005568145,0.002140831,0.0009110322,0.002606922,0.0003255634,0.01476847,0.7446455],"study_design_scores_gemma":[0.01609361,0.08116967,0.7982213,0.000977843,0.0006323986,0.001927382,0.005556514,0.0103036,0.00633667,0.002494835,0.07614619,0.0001399565],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9925167,0.0001743496,0.0006790832,0.001201042,0.00005538439,0.0006810497,0.0001543306,0.00009047797,0.004447632],"genre_scores_gemma":[0.9860408,0.0004203471,0.008513231,0.001016452,0.0001309769,0.001141902,0.0002545258,0.000004890007,0.002476954],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009003722,"threshold_uncertainty_score":0.03012049,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02280243610297622,"score_gpt":0.399479483140363,"score_spread":0.3766770470373867,"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."}}