{"id":"W4366307907","doi":"10.2196/44835","title":"Natural Language Processing for Clinical Laboratory Data Repository Systems: Implementation and Evaluation for Respiratory Viruses","year":2023,"lang":"en","type":"article","venue":"JMIR AI","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Sunnybrook Hospital; Sinai Health System; Vector Institute; Public Health Ontario; York University; University Health Network; University of Toronto","funders":"Canadian Institutes of Health Research; Hospital for Sick Children","keywords":"Computer science; Artificial intelligence; Natural language processing; Generalizability theory; Parsing; Classifier (UML); Machine learning; Information extraction; Task (project management)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.007174647,0.0009995921,0.0006046178,0.00108186,0.0006797489,0.001431358,0.003505564,0.001460827,0.003377863],"category_scores_gemma":[0.01856245,0.0005005164,0.0007107652,0.00104932,0.0007775513,0.00275,0.001896624,0.001853446,0.001687127],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002103599,"about_ca_system_score_gemma":0.003035901,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01841186,"about_ca_topic_score_gemma":0.0144426,"domain_scores_codex":[0.996345,0.001288313,0.000448976,0.0009081942,0.0008010579,0.0002085762],"domain_scores_gemma":[0.9899482,0.006411202,0.0004397181,0.0008638227,0.00186906,0.0004680636],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.004484861,0.005051716,0.02620248,0.003565798,0.0006983252,0.001803878,0.002757244,0.118805,0.03843767,0.002363567,0.04794212,0.7478873],"study_design_scores_gemma":[0.0008542371,0.001177171,0.009609471,0.0001646344,0.0001914282,0.0004437583,0.0008052597,0.9365124,0.0351666,0.002250185,0.0127124,0.0001124818],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7272162,0.001778118,0.1762781,0.002056489,0.0004003751,0.004765762,0.005966243,0.07561905,0.005919729],"genre_scores_gemma":[0.6406522,0.0008408894,0.3414703,0.0005868386,0.00006123612,0.001770648,0.01096854,0.0008535244,0.00279584],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01841186,"threshold_uncertainty_score":0.0379436,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1563436978837656,"score_gpt":0.5307190196558628,"score_spread":0.3743753217720972,"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."}}