{"id":"W4229005829","doi":"10.3390/app12094664","title":"Empirical Analysis of Forest Penalizing Attribute and Its Enhanced Variations for Android Malware Detection","year":2022,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Malware; Android (operating system); Computer science; Android malware; Machine learning; Artificial intelligence; Mobile malware; Support vector machine; Data mining; Computer security; Operating 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":[0.005044399,0.0006923302,0.0009876587,0.002785993,0.0006262052,0.0009804192,0.0008475383,0.0009332253,0.000590994],"category_scores_gemma":[0.01308458,0.0001667375,0.0009908547,0.00143827,0.0006014881,0.001488851,0.00046418,0.001189211,0.0002217665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006029049,"about_ca_system_score_gemma":0.0008832125,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003726935,"about_ca_topic_score_gemma":0.003614359,"domain_scores_codex":[0.9979579,0.0006348541,0.0001520684,0.0004610529,0.0005885863,0.000205406],"domain_scores_gemma":[0.9896033,0.006645323,0.0007779861,0.0008324898,0.001916093,0.0002248012],"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":[0.000778953,0.0006081976,0.1569095,0.000244086,0.0003031038,0.0003753052,0.0002527055,0.3750572,0.008591313,0.005910489,0.004045202,0.4469239],"study_design_scores_gemma":[0.000006930211,0.00009202721,0.01034046,0.00001250896,0.0000342341,0.0001111351,0.00003475133,0.9859616,0.001407988,0.001542074,0.0004425617,0.00001375577],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5393621,0.002001451,0.4543784,0.0005381554,0.0001205986,0.0001282014,0.0005105606,0.001452717,0.001507607],"genre_scores_gemma":[0.9405124,0.0002455873,0.05789972,0.0000684388,0.0000712535,0.00005837089,0.0006579156,0.00004318959,0.000443025],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005044399,"threshold_uncertainty_score":0.02667767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03652038637443307,"score_gpt":0.3144957016320316,"score_spread":0.2779753152575985,"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."}}