{"id":"W4396996782","doi":"10.1681/asn.20203110s1407b","title":"Code Status Variability in a Regional Hemodialysis Program","year":2020,"lang":"en","type":"article","venue":"Journal of the American Society of Nephrology","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kingston Health Sciences Centre","funders":"","keywords":"Hemodialysis; Code (set theory); Medicine; Intensive care medicine; Internal medicine; Computer science; Programming language","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":[0.001101775,0.0001029511,0.0004890661,0.00003259466,0.00006035413,0.00001412347,0.001182731,0.00004931248,0.00000718687],"category_scores_gemma":[0.0003340172,0.00007447121,0.0004153923,0.0009751447,0.0004897272,0.000108109,0.0002986134,0.0006716531,9.243338e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001029518,"about_ca_system_score_gemma":0.0003497697,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000326549,"about_ca_topic_score_gemma":0.00002579142,"domain_scores_codex":[0.9977494,0.000841781,0.0005529602,0.0002022398,0.0003623607,0.0002912015],"domain_scores_gemma":[0.9974814,0.0005751806,0.001255508,0.0003533257,0.0001943304,0.0001402315],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004839641,0.0007276114,0.6634514,0.0002185171,0.0004564908,0.00002129324,0.02488833,0.01518492,0.004453953,0.002067213,0.05011501,0.2379313],"study_design_scores_gemma":[0.0009148136,0.001784403,0.6737806,0.00002458935,0.00003521901,0.0001329298,0.0004578725,0.2156397,0.00003694116,0.002951334,0.1040691,0.00017251],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7382219,0.00009161459,0.02935237,0.2320239,0.00007595235,0.000172412,0.000002388435,0.00002754924,0.00003194546],"genre_scores_gemma":[0.8199754,0.0001081998,0.1565033,0.02326219,0.0001385544,0.000003597875,2.126748e-7,0.000006378395,0.000002251131],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2377588,"threshold_uncertainty_score":0.3036848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02990926964408099,"score_gpt":0.3180004049665761,"score_spread":0.2880911353224951,"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."}}