{"id":"W4316499895","doi":"10.1038/s41597-023-01945-2","title":"Author Correction: MIMIC-IV, a freely accessible electronic health record dataset","year":2023,"lang":"en","type":"erratum","venue":"Scientific Data","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":166,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"Computer science; Electronic health record; Information retrieval; Health records; Data science; World Wide Web; Political science; Health care","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01339781,0.00158396,0.001659863,0.006852895,0.002965498,0.005168234,0.003019614,0.002596822,0.1918794],"category_scores_gemma":[0.2119763,0.001121763,0.001567645,0.009312159,0.001779404,0.002564118,0.004332512,0.005821337,0.1053116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003422102,"about_ca_system_score_gemma":0.01099583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02538247,"about_ca_topic_score_gemma":0.0298221,"domain_scores_codex":[0.9844921,0.003272277,0.003692426,0.002019539,0.005886678,0.0006370196],"domain_scores_gemma":[0.8740664,0.03987772,0.007014852,0.01608085,0.06073967,0.002220589],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002857464,0.000003277628,0.0001757652,0.0001243213,0.00001268023,0.00006649373,0.00002994037,0.00004437416,0.00002410923,0.0005981275,0.9954554,0.00343696],"study_design_scores_gemma":[0.00009029893,0.00001291445,0.001317843,0.0006259962,0.00005800555,0.0003241621,0.0001310529,0.0002689062,0.000373043,0.002618008,0.9941252,0.0000545247],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.001631474,0.00135254,0.009374185,0.09036779,0.5758983,0.0002882282,0.2971381,0.005004091,0.01894522],"genre_scores_gemma":[0.03979577,0.004963281,0.03834924,0.07269885,0.06606124,0.001996699,0.3941874,0.02030661,0.361641],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1918794,"threshold_uncertainty_score":0.6419005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1006169606146817,"score_gpt":0.3922536860077259,"score_spread":0.2916367253930442,"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."}}