{"id":"W2403197697","doi":"","title":"Maximizing security standards. Technology can help achieve more than HIPAA requires.","year":2005,"lang":"en","type":"article","venue":"PubMed","topic":"Trade Secret Protection Methods","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Integrity Testing Laboratory (Canada)","funders":"","keywords":"Computer security; Computer science; Business; Internet privacy","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"],"consensus_categories":[],"category_scores_codex":[0.003268721,0.000276527,0.0004394327,0.0004413877,0.0008347052,0.00001885897,0.0004408862,0.0006688118,0.0002561494],"category_scores_gemma":[0.001610668,0.0002632116,0.0001013254,0.0007625481,0.0002136845,0.0002126914,0.0002752639,0.001951418,0.00004521299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001166007,"about_ca_system_score_gemma":0.0003469709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002604462,"about_ca_topic_score_gemma":0.001370331,"domain_scores_codex":[0.9959487,0.0008582614,0.0006785474,0.0005622385,0.0005506545,0.001401609],"domain_scores_gemma":[0.9980936,0.000236105,0.0003252298,0.0007462954,0.0002552941,0.0003434782],"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":[0.0004220489,0.0001338512,0.0372495,0.0003886904,0.0001285202,0.00002940682,0.007995463,0.0000242211,0.0004694235,0.01133226,0.009681704,0.9321449],"study_design_scores_gemma":[0.002923794,0.00008031599,0.1566956,0.0001294834,0.00006922828,0.00003303323,0.006123806,0.0001221664,0.004179339,0.0219145,0.8069574,0.0007712638],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6774052,0.001866116,0.01116227,0.2513982,0.003578449,0.01037835,0.0005582791,0.00391936,0.03973376],"genre_scores_gemma":[0.979065,0.0001048794,0.009357204,0.001736289,0.001013539,0.00627437,0.00001360877,0.00008390552,0.002351195],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9313737,"threshold_uncertainty_score":0.999982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06562601943385239,"score_gpt":0.3959159935149854,"score_spread":0.330289974081133,"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."}}