{"id":"W4297006047","doi":"10.3390/su141911934","title":"HealthGuard: An Intelligent Healthcare System Security Framework Based on Machine Learning","year":2022,"lang":"en","type":"article","venue":"Sustainability","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton","funders":"King Saud University; Future University in Egypt","keywords":"Computer science; Wearable computer; Computer security; Internet of Things; Wearable technology; Decision tree; Health care; Architecture; Artificial intelligence; Machine learning; Human–computer interaction; Embedded system","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":[0.001255874,0.0007389685,0.0005096885,0.0007398158,0.0003963511,0.00106622,0.001954603,0.0008557107,0.002314296],"category_scores_gemma":[0.001537245,0.0004054244,0.0007801764,0.0002360595,0.0007313204,0.001723459,0.001622115,0.001165234,0.0008692261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008999525,"about_ca_system_score_gemma":0.001697692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003373161,"about_ca_topic_score_gemma":0.003503738,"domain_scores_codex":[0.9994622,0.0001177258,0.0000433682,0.0001100014,0.0001991555,0.00006754126],"domain_scores_gemma":[0.999631,0.0001310676,0.00004977175,0.0000598383,0.00008211196,0.0000460975],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007673455,0.0005870641,0.009216779,0.0007251971,0.0003998358,0.0006752087,0.0005913018,0.3574672,0.02891958,0.0660294,0.03010357,0.5045175],"study_design_scores_gemma":[0.00004659597,0.0002184654,0.0007645678,0.0000583674,0.00005096618,0.0001471309,0.00003513389,0.9546633,0.01039987,0.01500157,0.01857311,0.00004095857],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009753794,0.0004742653,0.9654956,0.0005907257,0.00007215032,0.0003364475,0.0002019505,0.02005609,0.003019013],"genre_scores_gemma":[0.3970354,0.0007569072,0.5932934,0.000806693,0.00008157465,0.0005048156,0.001241095,0.0004812929,0.005798731],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003373161,"threshold_uncertainty_score":0.007742107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01351756489993267,"score_gpt":0.2890848215458945,"score_spread":0.2755672566459618,"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."}}