{"id":"W1999728176","doi":"10.1049/iet-ifs.2014.0099","title":"High accuracy android malware detection using ensemble learning","year":2015,"lang":"en","type":"article","venue":"IET Information Security","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":194,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Engineering and Physical Sciences Research Council","keywords":"Malware; Android malware; Computer science; Ensemble learning; Android (operating system); Machine learning; Artificial intelligence; 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":[0.001220928,0.0009005067,0.001147475,0.001673604,0.000557854,0.0008539439,0.0007369028,0.0007682911,0.0004511431],"category_scores_gemma":[0.003146484,0.0003503439,0.000734716,0.0007413749,0.0001994553,0.001352193,0.0008561719,0.0009768459,0.0004454326],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004215938,"about_ca_system_score_gemma":0.0004661626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003563538,"about_ca_topic_score_gemma":0.00516081,"domain_scores_codex":[0.9990978,0.0001709881,0.0000492413,0.0002005772,0.0003681235,0.0001133321],"domain_scores_gemma":[0.9981878,0.000713215,0.0001481596,0.000304898,0.0005882024,0.00005769793],"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":[0.0002650277,0.0003734373,0.02691609,0.00004733823,0.0002960926,0.0002548185,0.0001279457,0.2876241,0.022284,0.0009406446,0.002963032,0.6579074],"study_design_scores_gemma":[0.000001983075,0.00003881293,0.001751924,0.000002914261,0.00001511601,0.00005998013,0.00001063919,0.9939685,0.003548811,0.0003527986,0.0002406332,0.000007921171],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4066254,0.0005711757,0.58525,0.0002961234,0.0001148514,0.00007834556,0.0002660452,0.003728169,0.003069946],"genre_scores_gemma":[0.9205081,0.0001367722,0.07736647,0.00005534476,0.00004398436,0.00003102594,0.000366278,0.00003614592,0.001455843],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003563538,"threshold_uncertainty_score":0.007085621,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02087862960961052,"score_gpt":0.2689254753340033,"score_spread":0.2480468457243928,"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."}}