{"id":"W4404569722","doi":"10.48550/arxiv.2411.10342","title":"EHRs Data Harmonization Platform, an easy-to-use shiny app based on recodeflow for harmonizing and deriving clinical features","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministero dell'Università e della Ricerca; University of Toronto; Canadian Institutes of Health Research; European Commission; Dipartimenti di Eccellenza","keywords":"Harmonization; Computer science; Data science; Art","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.006202888,0.002105213,0.001270298,0.002275102,0.0005960646,0.002722022,0.002110052,0.001060443,0.05453129],"category_scores_gemma":[0.01886827,0.001242842,0.001817106,0.001381775,0.0006837978,0.003195322,0.006627057,0.001779999,0.03693642],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000516958,"about_ca_system_score_gemma":0.002211852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001541858,"about_ca_topic_score_gemma":0.001960355,"domain_scores_codex":[0.9967936,0.000702255,0.0003493001,0.0008885115,0.001043577,0.0002228232],"domain_scores_gemma":[0.9936726,0.003137734,0.000659601,0.001212719,0.00102255,0.0002948507],"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":[0.002320178,0.0002176058,0.007753743,0.001870667,0.0004673301,0.0007151483,0.001289421,0.001455496,0.007877342,0.007937966,0.71659,0.251505],"study_design_scores_gemma":[0.000824051,0.0002708353,0.01562083,0.0008103898,0.0002270471,0.000916273,0.0003476256,0.01423475,0.02197309,0.02368933,0.9206277,0.0004580389],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.006634833,0.001506977,0.266039,0.001451291,0.0008130082,0.002064137,0.1078294,0.5959125,0.01774891],"genre_scores_gemma":[0.05511635,0.001919564,0.4916574,0.004943585,0.00065142,0.008788499,0.2229518,0.1753824,0.038589],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.05453129,"threshold_uncertainty_score":0.1824253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.305942905694652,"score_gpt":0.3054172830560536,"score_spread":0.0005256226385983997,"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."}}