{"id":"W2922529937","doi":"10.18502/ijph.v48i2.826","title":"Massive Health Record Breaches Evidenced by the Office for Civil Rights Data","year":2019,"lang":"en","type":"article","venue":"Iranian Journal of Public Health","topic":"Information and Cyber Security","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Laurentian University","funders":"","keywords":"Data breach; Population; Internet privacy; Business; Law enforcement; Public health; Enforcement; Medicine; Computer security; Medical emergency; Environmental health; Computer science; Law; Political science; Pathology","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":[0.01382649,0.0003305552,0.0003370637,0.00557901,0.001789283,0.002564585,0.0009807597,0.0008483769,0.00722882],"category_scores_gemma":[0.09863436,0.0003237345,0.000463088,0.009239689,0.001659437,0.002520527,0.00365499,0.002317612,0.001086962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002418415,"about_ca_system_score_gemma":0.003998458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009715374,"about_ca_topic_score_gemma":0.01271255,"domain_scores_codex":[0.963262,0.009965449,0.006029715,0.003316832,0.01577968,0.001646357],"domain_scores_gemma":[0.7984341,0.07587597,0.0853655,0.01970046,0.01678797,0.003835942],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002701702,0.0001657281,0.8782344,0.0009146786,0.0001802597,0.0008013137,0.00573751,0.0004449575,0.001244076,0.004216475,0.03013674,0.0776537],"study_design_scores_gemma":[0.00001886309,0.0002524971,0.8786827,0.00238293,0.0001557426,0.002940628,0.01602717,0.001816589,0.004256374,0.003877127,0.089501,0.00008836784],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8635762,0.005271233,0.01137394,0.03091186,0.0006448958,0.0008952639,0.03814261,0.0006506847,0.04853346],"genre_scores_gemma":[0.9770607,0.001832056,0.006533084,0.002601558,0.0002718012,0.0002445013,0.00857477,0.00008313774,0.002798447],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01382649,"threshold_uncertainty_score":0.07312232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09163039051515809,"score_gpt":0.3277738468675239,"score_spread":0.2361434563523658,"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."}}