{"id":"W4313575350","doi":"10.2196/44547","title":"An Ontology-Based Approach for Consolidating Patient Data Standardized With European Norm/International Organization for Standardization 13606 (EN/ISO 13606) Into Joint Observational Medical Outcomes Partnership (OMOP) Repositories: Description of a Methodology","year":2023,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Instituto de Salud Carlos III; Barcelona Supercomputing Center; European Commission","keywords":"Computer science; Standardization; Ontology; Information retrieval; Data mining; Data science","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.003145929,0.0002148007,0.0004226154,0.0001259973,0.0001756647,0.00005418049,0.0006502338,0.000427555,0.00002309052],"category_scores_gemma":[0.009860973,0.0001649617,0.00007265314,0.0002694848,0.0003819439,0.00004640371,0.0002330041,0.0001699078,9.434666e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004978454,"about_ca_system_score_gemma":0.0007545743,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008544517,"about_ca_topic_score_gemma":0.00002743923,"domain_scores_codex":[0.996973,0.00033599,0.001068654,0.0003264182,0.0009977065,0.0002982256],"domain_scores_gemma":[0.9975187,0.0004164464,0.000545555,0.000510849,0.0007774923,0.0002309731],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0157501,0.005445409,0.2250537,0.01140242,0.006543894,0.00008935868,0.06599457,0.01393145,0.04235177,0.02702281,0.1592053,0.4272092],"study_design_scores_gemma":[0.02560563,0.009035786,0.01670964,0.0008204631,0.0005078964,0.0001945064,0.03193534,0.7496508,0.02995455,0.001381785,0.1321601,0.002043469],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1027928,0.00001471801,0.8946373,0.001165027,0.0002890803,0.000595722,0.0002888343,0.0001013046,0.0001152704],"genre_scores_gemma":[0.4513311,0.00002400968,0.5165487,0.001281601,0.0003634387,0.0001574841,0.03021426,0.0000492509,0.00003020024],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7357194,"threshold_uncertainty_score":0.9984794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1379573935162494,"score_gpt":0.3810201849519069,"score_spread":0.2430627914356575,"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."}}