{"id":"W2031805859","doi":"10.1109/mobilesoft.2015.38","title":"Detecting Antipatterns in Android Apps","year":2015,"lang":"en","type":"preprint","venue":"","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Université du Québec à Montréal","keywords":"Android (operating system); Computer science; Operating system; World Wide Web","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005465142,0.0002535302,0.000309916,0.0004116858,0.00003389962,0.0001729048,0.001336634,0.0002609541,0.00001111996],"category_scores_gemma":[0.0001101501,0.0002586345,0.00007096365,0.0003239347,0.00002224889,0.0003345645,0.002885895,0.0008198731,0.0000312726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000213247,"about_ca_system_score_gemma":0.0001160773,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002333337,"about_ca_topic_score_gemma":0.0002148644,"domain_scores_codex":[0.9981709,0.00007451179,0.0003722278,0.000787881,0.0002785689,0.0003158955],"domain_scores_gemma":[0.9984248,0.00005159382,0.0001843894,0.001113235,0.0001325703,0.00009341515],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002222589,0.0002034438,0.006069364,0.0003299506,0.00003908308,0.0003690723,0.002085937,0.006409255,0.002645901,0.005071451,0.002865436,0.9738889],"study_design_scores_gemma":[0.001139897,0.0003215963,0.00264539,0.0008436182,0.00001124933,0.0002562445,0.0001822849,0.2323939,0.2727879,0.4758413,0.01065756,0.00291908],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0174917,0.0001111288,0.9740056,0.000167681,0.0006576484,0.0003430329,0.000002213606,0.001719187,0.005501768],"genre_scores_gemma":[0.7463346,0.00002926459,0.2530485,0.0001675383,0.00007407096,0.00008887125,0.000001923455,0.00001998528,0.0002352457],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9709698,"threshold_uncertainty_score":0.9999866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03687840769146597,"score_gpt":0.3049851365521173,"score_spread":0.2681067288606513,"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."}}