{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003228564,0.0001450403,0.0002158304,0.000221175,0.0002557671,0.0001427357,0.0001502514,0.00003296514,0.0001297192],"category_scores_gemma":[0.0003148111,0.0000871907,0.0001293727,0.0005087009,0.0003471458,0.0004647846,0.0001758197,0.000141683,0.0001399987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002772868,"about_ca_system_score_gemma":0.0003237553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001335539,"about_ca_topic_score_gemma":0.000001692419,"domain_scores_codex":[0.9977744,0.0000440476,0.0002300297,0.0003072603,0.001110828,0.0005334218],"domain_scores_gemma":[0.9976077,0.00009346816,0.0000579495,0.000393079,0.001103239,0.0007445823],"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":[0.008158674,0.004072926,0.008402764,0.0007139131,0.0001828164,0.000006552641,0.0004305412,0.000002881424,0.000007324526,0.0004491622,0.01258864,0.9649838],"study_design_scores_gemma":[0.01564244,0.02138591,0.6399577,0.001440441,0.0001134912,4.669325e-7,0.0002714937,0.00747119,0.0001079397,0.00192816,0.3112912,0.0003896481],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9777203,0.00005102377,0.002389604,0.000873322,0.00007835719,0.007174065,0.0003394442,0.00009921614,0.01127468],"genre_scores_gemma":[0.9962754,0.00001033716,0.0005634088,0.00007655168,0.000149643,0.001649921,0.0005333154,0.00002248494,0.0007189742],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9645941,"threshold_uncertainty_score":0.3555534,"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."}}