{"id":"W4297461828","doi":"10.1109/tvcg.2022.3209444","title":"<i>ChartWalk</i>: Navigating large collections of text notes in electronic health records for clinical chart review","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Addiction and Mental Health; University of Toronto","funders":"","keywords":"Computer science; Chart; Health records; Electronic health record; Information retrieval; Data visualization; Data science; Visualization; World Wide Web; Data mining; 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":[0.01008792,0.001819124,0.0005169462,0.002123031,0.0010363,0.003377368,0.002252095,0.001737158,0.0114917],"category_scores_gemma":[0.03226516,0.0007134726,0.0009351644,0.001731759,0.00136957,0.004391996,0.003733359,0.001298996,0.00318929],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007338288,"about_ca_system_score_gemma":0.001921492,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001052573,"about_ca_topic_score_gemma":0.002210831,"domain_scores_codex":[0.9930418,0.004491021,0.0005834086,0.0007504855,0.0008857553,0.0002476677],"domain_scores_gemma":[0.9671332,0.02210282,0.001729396,0.003831871,0.003651555,0.001551213],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002084704,0.0006826941,0.009074043,0.007122203,0.0002543203,0.002533717,0.03928327,0.00653834,0.1019657,0.02136311,0.1648687,0.6442292],"study_design_scores_gemma":[0.0007926759,0.003115761,0.01879115,0.003767052,0.0004075741,0.004245387,0.01162521,0.07602939,0.1074132,0.03589125,0.7370533,0.0008680762],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02272335,0.0003307711,0.9196552,0.002613122,0.0002622298,0.002556719,0.003076029,0.04248987,0.006292708],"genre_scores_gemma":[0.058306,0.0002306485,0.9314671,0.0005150418,0.00006935382,0.001912111,0.001782464,0.00264367,0.003073546],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0114917,"threshold_uncertainty_score":0.05335069,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03657597239781057,"score_gpt":0.3798537146484933,"score_spread":0.3432777422506827,"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."}}