{"id":"W2545900688","doi":"10.1109/inmic.2008.4777723","title":"The national strategies for Electronic Health Record in three developed countries: General status","year":2008,"lang":"en","type":"article","venue":"","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Electronic health record; Health records; Health care; Politics; Healthcare system; Population; Business; Medicine; Economic growth; Political science; Environmental health","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.007263228,0.0004123242,0.0002617193,0.002682332,0.00340529,0.005974624,0.001200936,0.001859683,0.004111614],"category_scores_gemma":[0.007403946,0.0002804296,0.0003341836,0.003614196,0.001940041,0.003836974,0.005183889,0.001273632,0.0004968534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01496085,"about_ca_system_score_gemma":0.04335568,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1417982,"about_ca_topic_score_gemma":0.1362588,"domain_scores_codex":[0.9952265,0.0012502,0.0006939654,0.0003585086,0.001426377,0.001044401],"domain_scores_gemma":[0.9944296,0.001048838,0.0006407221,0.0003107792,0.002644479,0.00092562],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001864474,0.0004010726,0.1087881,0.001723466,0.00006671143,0.001118903,0.01226379,0.001088856,0.001594558,0.3647379,0.05425332,0.4537769],"study_design_scores_gemma":[0.00007102484,0.0003281522,0.2066596,0.001994936,0.0001024011,0.001458576,0.02275211,0.0009901375,0.003256618,0.01068166,0.7516006,0.000104231],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2448477,0.06339164,0.01386381,0.1991726,0.000810931,0.002487506,0.003049797,0.0004199302,0.4719562],"genre_scores_gemma":[0.7970008,0.0330043,0.05564266,0.03123578,0.0001937505,0.00214156,0.002668317,0.00006578308,0.07804707],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1417982,"threshold_uncertainty_score":0.2819458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.124815263235761,"score_gpt":0.4556971630456538,"score_spread":0.3308818998098927,"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."}}