{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008827553,0.002771909,0.001367795,0.00520833,0.001039726,0.005372138,0.003490587,0.001786703,0.06039182],"category_scores_gemma":[0.03969884,0.001151791,0.001282871,0.00389639,0.0008066127,0.006334949,0.007885338,0.00247192,0.02614248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001617914,"about_ca_system_score_gemma":0.002561329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003931088,"about_ca_topic_score_gemma":0.004572073,"domain_scores_codex":[0.9942978,0.001136826,0.0008937216,0.001076778,0.002360443,0.0002344496],"domain_scores_gemma":[0.9696144,0.0147668,0.00234141,0.00582096,0.005379548,0.002076898],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001818098,0.0003076224,0.004729501,0.001508903,0.0001437523,0.0009231221,0.00124728,0.002402413,0.005256208,0.007316286,0.6532911,0.3210557],"study_design_scores_gemma":[0.0004045019,0.0001934526,0.005401256,0.0006182418,0.0000796552,0.000558254,0.0004465064,0.01739445,0.01128562,0.01356381,0.9498198,0.0002345499],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"software","genre_gemma":"methods","genre_scores_codex":[0.01278654,0.001265451,0.2111298,0.005131392,0.002413173,0.001644638,0.1014098,0.6345719,0.02964739],"genre_scores_gemma":[0.07433262,0.002143663,0.5313172,0.005561588,0.001132068,0.00371335,0.2550169,0.07056973,0.05621289],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.06039182,"threshold_uncertainty_score":0.2020307,"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."}}