{"id":"W4387207836","doi":"10.1016/j.ijrobp.2023.06.239","title":"Operational Ontology for Radiation Oncology (OORO): A Professional Society-Based, Multi-Stakeholder Consensus Driven Informatics Standard Supporting Clinical and Research Use of Real-World Data","year":2023,"lang":"en","type":"article","venue":"International Journal of Radiation Oncology*Biology*Physics","topic":"Lung Cancer Diagnosis and Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Nova Scotia Health Authority; Dalhousie University","funders":"Seagen; NRG Oncology","keywords":"Standardization; Medicine; Radiation oncology; Stakeholder; Medical physics; Prostate cancer; Professional association; Informatics; Clinical Oncology; Health informatics tools; Data science; Internal medicine; Cancer; Radiation therapy; Computer science; Public relations","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":[],"consensus_categories":[],"category_scores_codex":[0.05841082,0.001325543,0.001702824,0.009464018,0.00508615,0.012338,0.005160323,0.004515227,0.002604972],"category_scores_gemma":[0.08431019,0.001305057,0.002886746,0.00799056,0.004841105,0.01414286,0.01462161,0.006325408,0.002079024],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006178893,"about_ca_system_score_gemma":0.02895234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0125997,"about_ca_topic_score_gemma":0.01364058,"domain_scores_codex":[0.9476179,0.01707376,0.01430651,0.004258205,0.01463974,0.002103847],"domain_scores_gemma":[0.9188437,0.02541018,0.007602392,0.0239393,0.01973523,0.004469278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001537353,0.000459602,0.004731216,0.001546446,0.0002085998,0.0004277052,0.008747056,0.007567159,0.009207617,0.8038974,0.04053004,0.1225235],"study_design_scores_gemma":[0.00006077758,0.0001308874,0.003237971,0.001590377,0.000184331,0.000633089,0.004807146,0.03987574,0.008566177,0.4410723,0.499614,0.0002271722],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006354429,0.0001872377,0.9647129,0.004477515,0.0003964155,0.001671372,0.002670889,0.004978337,0.0145509],"genre_scores_gemma":[0.0692635,0.0003827332,0.9091362,0.001757629,0.0001702192,0.001925079,0.01191222,0.001558281,0.003894177],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05841082,"threshold_uncertainty_score":0.3089097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2920016131027424,"score_gpt":0.5347558410915471,"score_spread":0.2427542279888047,"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."}}