{"id":"W2132746538","doi":"10.1109/congress.2009.14","title":"Electronic Personal Health Record Systems: A Brief Review of Privacy, Security, and Architectural Issues","year":2009,"lang":"en","type":"review","venue":"","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":72,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Variety (cybernetics); Internet privacy; Personally identifiable information; Information privacy; Computer security; Health care; Computer science; Medical prescription; Architecture; Medical information; Business; Knowledge management; Medicine; Nursing","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.007560791,0.001142837,0.009028502,0.0004902057,0.0006083862,0.00002198563,0.0007948386,0.0009257228,0.0004074419],"category_scores_gemma":[0.0005835055,0.0008512018,0.0007127862,0.0008993042,0.000114687,0.0001146443,0.0003123902,0.004606189,0.0001614904],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002757206,"about_ca_system_score_gemma":0.01733637,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008258198,"about_ca_topic_score_gemma":0.001819694,"domain_scores_codex":[0.9799757,0.009159321,0.00566193,0.001278936,0.0008909488,0.003033154],"domain_scores_gemma":[0.9918348,0.001589621,0.004328016,0.00114699,0.0003549476,0.0007456373],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000005609511,0.00002781452,0.000009620496,0.5207843,0.00009545973,0.000001815073,0.0005034785,2.063925e-9,7.308972e-9,0.001261996,0.02585831,0.4514517],"study_design_scores_gemma":[0.0002197204,0.000597859,0.000002026813,0.3914498,0.0001814075,0.000193221,0.00009694588,0.000008212854,4.740291e-9,0.00009600737,0.6067822,0.0003725601],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000006994808,0.9789714,0.00002819093,0.003113537,0.0007733145,0.01368439,0.0001195754,0.0002589797,0.003043597],"genre_scores_gemma":[0.00001053766,0.98928,0.0001254899,0.002709836,0.001216389,0.001078138,0.0002259137,0.0001690109,0.005184677],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.5809239,"threshold_uncertainty_score":0.9993939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08441904287598469,"score_gpt":0.4907236899965089,"score_spread":0.4063046471205242,"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."}}