{"id":"W4383618376","doi":"10.1093/jamiaopen/ooad046","title":"AnnoDash, a clinical terminology annotation dashboard","year":2023,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; SickKids Foundation; Hospital for Sick Children","funders":"","keywords":"Computer science; SNOMED CT; Information retrieval; Terminology; Ontology; Annotation; Dashboard; Ranking (information retrieval); Interoperability; Interface (matter); Data science; World Wide Web; Artificial intelligence","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":[0.0005209784,0.00009706417,0.0001745109,0.0000403007,0.000075109,0.00004532059,0.0005153753,0.0002834991,0.00003239828],"category_scores_gemma":[0.0004922849,0.00008294483,0.00006490615,0.0001578985,0.0001824498,0.000003337156,0.0005652845,0.0001147835,0.0003656861],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004983133,"about_ca_system_score_gemma":0.00007977582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002726459,"about_ca_topic_score_gemma":0.00003055538,"domain_scores_codex":[0.9989378,0.0001227533,0.0002515367,0.0003641849,0.00008071306,0.0002430389],"domain_scores_gemma":[0.9994259,0.00004732259,0.00006940066,0.0003413005,0.00004062432,0.00007540553],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002015961,0.00009422905,0.03459651,0.00001531332,0.00009074828,0.00005981467,0.0001066326,0.000007085153,0.0223239,0.0001871344,0.3932596,0.5490574],"study_design_scores_gemma":[0.001002847,0.000560097,0.1443693,0.00001201838,0.00001173805,0.00001715147,0.0001916551,0.0002301916,0.002699368,0.0004190517,0.8502975,0.0001891568],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9891563,0.0001014639,0.0003027482,0.002241244,0.0005627591,0.0002268051,0.00001929073,0.00008894353,0.007300424],"genre_scores_gemma":[0.9809876,0.0002848117,0.003392641,0.001946128,0.0005757763,0.00007840583,0.0004781957,0.00002582225,0.01223062],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5488683,"threshold_uncertainty_score":0.4700277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09907901780984156,"score_gpt":0.435239821340387,"score_spread":0.3361608035305454,"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."}}