{"id":"W2296273445","doi":"","title":"Quality of care metric reporting from clinical narratives: Assessing ontology components","year":2014,"lang":"en","type":"article","venue":"","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Metric (unit); Ontology; Health care; Quality (philosophy); Computer science; Data extraction; Data science; Quality management; Data quality; Knowledge management; Information retrieval; Data mining; MEDLINE; Business; Operations management; Engineering; Political science; Management system; Marketing","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03073283,0.0005318908,0.0004636388,0.01149988,0.001112858,0.004409979,0.001050497,0.0007311566,0.001010573],"category_scores_gemma":[0.1498461,0.0002340416,0.0009841603,0.009544805,0.001015555,0.003413301,0.003010265,0.001042753,0.0002540966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003203429,"about_ca_system_score_gemma":0.005327814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006724521,"about_ca_topic_score_gemma":0.006300575,"domain_scores_codex":[0.9733282,0.01144134,0.005817151,0.001559022,0.007412108,0.0004421323],"domain_scores_gemma":[0.8031427,0.1433586,0.02280266,0.006637484,0.02311343,0.0009452121],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000874988,0.0005329305,0.3070379,0.005825412,0.0008965607,0.001079815,0.0193231,0.01461591,0.01580275,0.03580857,0.01373927,0.5844628],"study_design_scores_gemma":[0.0002126639,0.0006869826,0.2760194,0.006723008,0.001686944,0.002480354,0.03728646,0.3610723,0.08787021,0.08382884,0.1416035,0.0005292672],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4680042,0.002260548,0.4862567,0.006046216,0.0002526363,0.004817231,0.01737106,0.0015476,0.01344388],"genre_scores_gemma":[0.5235136,0.0007623206,0.4621654,0.0002937682,0.00004609811,0.001417686,0.01106933,0.0001040102,0.0006278266],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9692672,"threshold_uncertainty_score":0.1625327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1336655732483018,"score_gpt":0.4496565336896625,"score_spread":0.3159909604413608,"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."}}