{"id":"W3110102192","doi":"10.1108/el-07-2020-0219","title":"Achieving data security and privacy across healthcare applications using cyber security mechanisms","year":2020,"lang":"en","type":"article","venue":"The Electronic Library","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Health care; Big data; Internet privacy; Information privacy; Computer security; Computer science; Business; Information security; Analytics; Data science; Data mining","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":["open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.000446369,0.000222223,0.0002223495,0.0000312649,0.0005558491,0.000428082,0.03662394,0.0001285406,0.00001218666],"category_scores_gemma":[0.0008024537,0.0001821759,0.00003342435,0.0008176967,0.0001441012,0.003289053,0.1673431,0.0009117943,0.00001370626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005410535,"about_ca_system_score_gemma":0.0003145808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003851345,"about_ca_topic_score_gemma":0.00000687857,"domain_scores_codex":[0.9975289,0.0001862761,0.0002724725,0.0009415756,0.0002690822,0.0008017714],"domain_scores_gemma":[0.9895298,0.000178872,0.0001518301,0.009986936,0.00001649311,0.0001360224],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004206749,0.0001303351,0.001330215,0.0003384336,0.0001683026,0.00002046064,0.005119978,0.000007009244,0.002600041,0.9137918,0.04574829,0.03070304],"study_design_scores_gemma":[0.0001582212,0.00004996156,0.00006700158,0.00001775786,0.000008983044,0.00003595866,0.000101365,0.1527559,0.002164005,0.8330837,0.01133186,0.0002252808],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.06646784,0.00585535,0.4490944,0.4744417,0.00009049772,0.001042434,0.0002973969,0.00256055,0.0001497533],"genre_scores_gemma":[0.9400877,0.0005492667,0.0557063,0.003351972,0.0001367663,0.00002815774,0.0001029467,0.00003339092,0.000003474623],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8736199,"threshold_uncertainty_score":0.9685884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04772210030458254,"score_gpt":0.3022853345222798,"score_spread":0.2545632342176973,"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."}}