{"id":"W2165748167","doi":"10.1373/49.4.624","title":"LOINC, a Universal Standard for Identifying Laboratory Observations: A 5-Year Update","year":2003,"lang":"en","type":"article","venue":"Clinical Chemistry","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":580,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children","funders":"U.S. National Library of Medicine; National Heart, Lung, and Blood Institute; Agency for Healthcare Research and Quality; Centers for Disease Control and Prevention","keywords":"Identifier; Health Insurance Portability and Accountability Act; Computer science; World Wide Web; Database; Medicine; Confidentiality; Computer security","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004127252,0.0001786983,0.000492147,0.00002170482,0.0005787447,0.0000140247,0.0002544684,0.0005663526,0.0005725865],"category_scores_gemma":[0.005566611,0.0001829224,0.0001550447,0.000271566,0.00009418416,0.0001241226,0.00005355847,0.001154506,0.0002002977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005550068,"about_ca_system_score_gemma":0.003739412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001000741,"about_ca_topic_score_gemma":0.000026558,"domain_scores_codex":[0.9964905,0.0005974313,0.001389647,0.0004883909,0.000238907,0.0007950846],"domain_scores_gemma":[0.9958044,0.002207433,0.0004965608,0.0005569287,0.0005620619,0.0003726617],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008823908,0.000402914,0.5856747,0.008778487,0.000307666,0.00003400664,0.0006384155,0.000003933564,0.003324693,0.03205534,0.3668775,0.001019973],"study_design_scores_gemma":[0.003307706,0.0000790675,0.0007937578,0.0003743142,0.00004075304,0.000001363016,0.001730562,0.00004367352,0.0008665319,0.001893991,0.9906088,0.0002595036],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9739378,0.0009193982,0.005138106,0.002763376,0.002594201,0.0020613,0.0004027287,0.0003976023,0.0117855],"genre_scores_gemma":[0.9393925,0.0008484009,0.01956661,0.007243745,0.003921965,0.001136608,0.0002971036,0.0002618274,0.02733123],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6237313,"threshold_uncertainty_score":0.7459359,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2147281489805517,"score_gpt":0.5147618049490499,"score_spread":0.3000336559684982,"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."}}