{"id":"W1992634704","doi":"10.2196/resprot.3815","title":"A Participatory Approach to Designing and Enhancing Integrated Health Information Technology Systems for Veterans: Protocol","year":2015,"lang":"en","type":"article","venue":"JMIR Research Protocols","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Quality Enhancement Research Initiative; Office of Research and Development; Health Services Research and Development; U.S. Department of Veterans Affairs","keywords":"Veterans Affairs; Health information technology; Health care; Health information exchange; Protocol (science); Health informatics; Citizen journalism; HRHIS; Information system; Knowledge management; Information exchange; Medicine; Nursing; Health information; Computer science; Health policy; Public health; Alternative medicine; World Wide Web; Engineering; Telecommunications; Political 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.07536447,0.002366012,0.001448941,0.002925186,0.009527767,0.003671677,0.004357338,0.004674067,0.07749941],"category_scores_gemma":[0.07314947,0.002628691,0.001754594,0.003137855,0.003321624,0.003582937,0.00668526,0.006824685,0.009289439],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009709159,"about_ca_system_score_gemma":0.03820951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007068282,"about_ca_topic_score_gemma":0.01251187,"domain_scores_codex":[0.9562562,0.03288491,0.00407455,0.002119075,0.002285254,0.002380053],"domain_scores_gemma":[0.9364418,0.03154336,0.00278692,0.009423904,0.01626638,0.003537609],"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":[0.01753015,0.01127459,0.003372636,0.04221143,0.000285514,0.003132427,0.115433,0.00761055,0.01057399,0.1283163,0.2454753,0.4147842],"study_design_scores_gemma":[0.01695009,0.004746419,0.004134759,0.01251624,0.00020765,0.0004085235,0.03319075,0.003430818,0.006208684,0.03315012,0.8846848,0.0003710745],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"protocol","genre_gemma":"protocol","genre_scores_codex":[0.002243455,0.00008959945,0.01364255,0.0007412031,0.0002097041,0.9756773,0.001942255,0.0001073345,0.005346706],"genre_scores_gemma":[0.00110318,0.00006715439,0.009829479,0.0001780313,0.000009599541,0.9880081,0.0001299395,0.00000682139,0.000667776],"genre_candidate":"protocol","genre_consensus":"protocol","teacher_disagreement_score":0.07749941,"threshold_uncertainty_score":0.3985702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.603364688804051,"score_gpt":0.6611888984911413,"score_spread":0.05782420968709023,"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."}}