{"id":"W2130865790","doi":"10.1136/amiajnl-2014-002707","title":"Query Health: standards-based, cross-platform population health surveillance","year":2014,"lang":"en","type":"article","venue":"Journal of the American Medical Informatics Association","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; U.S. Food and Drug Administration; U.S. National Library of Medicine; Agency for Healthcare Research and Quality; National Institutes of Health; Hamilton Health Sciences Foundation","keywords":"Computer science; Public health informatics; Health informatics; Population; Population health; Data quality; Interoperability; Public health; Data science; HRHIS; World Wide Web; Health policy; Medicine; Environmental health; Business","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1326091,0.001725993,0.001158273,0.006958884,0.001924738,0.009621062,0.007060542,0.002473613,0.002863976],"category_scores_gemma":[0.1139475,0.001226214,0.001985508,0.006578566,0.003376999,0.01490302,0.01097209,0.003575954,0.001901998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005798248,"about_ca_system_score_gemma":0.0194912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02438178,"about_ca_topic_score_gemma":0.0104584,"domain_scores_codex":[0.9115127,0.03809605,0.01160388,0.009701983,0.02649744,0.00258789],"domain_scores_gemma":[0.870755,0.04276127,0.009579528,0.0347955,0.03838677,0.00372198],"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":[0.001184695,0.001202836,0.07086445,0.003030676,0.0006880009,0.000695363,0.01151895,0.02205441,0.01985404,0.2811663,0.1298717,0.4578686],"study_design_scores_gemma":[0.0007602391,0.001897623,0.04614572,0.003053359,0.0006077593,0.001198026,0.005826558,0.1747058,0.06309505,0.1543535,0.547496,0.0008603455],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01345114,0.0007038789,0.9164126,0.008382777,0.000274901,0.002841834,0.004658748,0.04198254,0.01129164],"genre_scores_gemma":[0.1294606,0.0007946123,0.8382418,0.002949546,0.0002937955,0.002382846,0.01866437,0.004206824,0.003005609],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1326091,"threshold_uncertainty_score":0.7013125,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02232772215575296,"score_gpt":0.4458368622317493,"score_spread":0.4235091400759964,"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."}}