{"id":"W4401823954","doi":"10.3233/shti240659","title":"Linking Health Terminologies: A Unified Approach to the WHO Family of International Classifications","year":2024,"lang":"en","type":"article","venue":"Studies in health technology and informatics","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Health Information","funders":"World Health Organization","keywords":"Interoperability; Computer science; Linkage (software); Informatics; Health informatics; Data science; Knowledge management; World Wide Web; Health care; Engineering","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":[0.03479806,0.001090089,0.001672705,0.03251782,0.003572174,0.01251032,0.003773403,0.002942375,0.002998313],"category_scores_gemma":[0.04014578,0.0008081949,0.002239613,0.02442835,0.008235027,0.0201748,0.006902563,0.004944548,0.002003924],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005673199,"about_ca_system_score_gemma":0.01563505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00811826,"about_ca_topic_score_gemma":0.005739131,"domain_scores_codex":[0.9761091,0.01227394,0.003863063,0.00186924,0.005160096,0.0007244842],"domain_scores_gemma":[0.9717277,0.01123196,0.002572044,0.005461351,0.008067259,0.0009397065],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001195901,0.00001998667,0.00085544,0.000256615,0.00002860235,0.0001113161,0.002633105,0.00077076,0.0003913225,0.9154325,0.01030859,0.06917982],"study_design_scores_gemma":[0.00001692836,0.00004112413,0.001219408,0.001389576,0.00009181063,0.0005061363,0.00272322,0.006276994,0.0006732802,0.4788143,0.5081729,0.00007436931],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002062448,0.00357216,0.947388,0.008348458,0.001268446,0.0005126917,0.0009732173,0.0008796597,0.03499494],"genre_scores_gemma":[0.02681451,0.003377034,0.9605241,0.00182931,0.0009200799,0.0009527742,0.002349449,0.0003205679,0.002912102],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03479806,"threshold_uncertainty_score":0.1840319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08491963788981843,"score_gpt":0.386373813598148,"score_spread":0.3014541757083296,"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."}}