{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007968229,0.0001424623,0.0003650142,0.0001429714,0.0003855899,0.0004237324,0.002996859,0.00005095744,0.00005432377],"category_scores_gemma":[0.0001604621,0.00009139428,0.00009374972,0.0003862429,0.00003970958,0.002954946,0.0001915326,0.0003852066,0.00005295778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002160311,"about_ca_system_score_gemma":0.002533171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002780941,"about_ca_topic_score_gemma":0.0003761274,"domain_scores_codex":[0.9971186,0.0005053106,0.0009941725,0.0002343617,0.0005752284,0.0005723158],"domain_scores_gemma":[0.99639,0.0003270851,0.001415608,0.000990949,0.0003782107,0.0004981647],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003254386,0.0001745389,0.0003344529,0.0002085519,0.00007228486,0.000002008034,0.02076131,0.000006362802,0.000006287833,0.03970919,0.5576186,0.3810739],"study_design_scores_gemma":[0.00107911,0.0007200124,0.00134126,0.0001145534,0.000002577138,0.000142946,0.0006879146,0.009664251,0.000005629468,0.001252204,0.9848372,0.0001523909],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009487068,0.001367047,0.6364703,0.3482872,0.002187524,0.000882591,0.0001014275,0.00005924685,0.001157687],"genre_scores_gemma":[0.9412563,0.000239794,0.02379261,0.03368552,0.0004502312,0.000006481645,0.00004601348,0.00001795479,0.0005050559],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9317693,"threshold_uncertainty_score":0.5568959,"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."}}