{"id":"W4281620354","doi":"10.3233/shti220086","title":"OpenMRS Analytics Engine: A FHIR Based Approach","year":2022,"lang":"en","type":"article","venue":"Studies in health technology and informatics","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Google (Canada)","funders":"","keywords":"Analytics; Interoperability; Scalability; Computer science; Pipeline (software); Data science; Architecture; Database; World Wide Web; Operating system","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":[0.005821839,0.001689876,0.001344332,0.00340752,0.001314323,0.007008911,0.00549509,0.002132086,0.01221746],"category_scores_gemma":[0.01031697,0.001089822,0.002602758,0.001932889,0.001145914,0.006974524,0.007824916,0.002695093,0.007081208],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001623624,"about_ca_system_score_gemma":0.003115447,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01084044,"about_ca_topic_score_gemma":0.01157381,"domain_scores_codex":[0.9937329,0.0007372213,0.0007555509,0.001607978,0.002624933,0.0005415119],"domain_scores_gemma":[0.9959788,0.001172366,0.0002413264,0.001155057,0.001125214,0.000327147],"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":[0.002643197,0.001332336,0.01060914,0.002259923,0.0008597937,0.003376672,0.002839121,0.03668582,0.0614103,0.2085766,0.216574,0.4528331],"study_design_scores_gemma":[0.0002817962,0.0003762304,0.00273844,0.0004101901,0.0003092046,0.0008841908,0.0007620791,0.5433098,0.0686527,0.1006078,0.2812541,0.0004136031],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006419477,0.000389425,0.8606734,0.00159909,0.0002820664,0.001173555,0.007075122,0.1099357,0.01245216],"genre_scores_gemma":[0.09720682,0.0004511213,0.8472553,0.001643681,0.0002960462,0.000650299,0.02789124,0.006191727,0.01841374],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01221746,"threshold_uncertainty_score":0.0408715,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2485296359890251,"score_gpt":0.4559431301719775,"score_spread":0.2074134941829525,"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."}}