{"id":"W3164128247","doi":"10.2196/20407","title":"The Clinical Decision Support System AMPEL for Laboratory Diagnostics: Implementation and Technical Evaluation","year":2021,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Clinical decision support system; Computer science; Decision support system; Medical emergency; Health informatics; Health care; Medicine; Medical physics; Artificial intelligence; Public health; Nursing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01772504,0.000158072,0.0004042079,0.00005233211,0.001009282,0.00003815727,0.0002324622,0.0005808204,0.0002103459],"category_scores_gemma":[0.007998104,0.000108226,0.0000760619,0.0002525602,0.0001260152,0.0001892142,0.0001808617,0.0009791791,0.0001440673],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005707661,"about_ca_system_score_gemma":0.00718784,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001120842,"about_ca_topic_score_gemma":0.0005807769,"domain_scores_codex":[0.9934904,0.001136297,0.003078507,0.0001848394,0.001404371,0.0007056106],"domain_scores_gemma":[0.9845687,0.01255392,0.0007128768,0.0004576988,0.001193188,0.0005136643],"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":[0.0001248387,0.0001001759,0.02239417,0.002711357,0.00006468357,0.000007308507,0.003138088,5.608242e-7,0.000005034135,0.01803391,0.4267571,0.5266627],"study_design_scores_gemma":[0.008059254,0.0007216682,0.01899497,0.001538996,0.0001427297,0.00006758541,0.06737245,0.02086267,0.00001815632,0.0009420042,0.8809243,0.0003552081],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7980958,0.003923613,0.1188177,0.01565271,0.01769522,0.03263512,0.0005246244,0.001031271,0.01162395],"genre_scores_gemma":[0.9231275,0.008223292,0.02412956,0.0178384,0.005774677,0.0189358,0.001318118,0.0001678613,0.0004847556],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5263075,"threshold_uncertainty_score":0.9984405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08220354098883886,"score_gpt":0.5594160020215506,"score_spread":0.4772124610327118,"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."}}