{"id":"W4312856608","doi":"10.1109/icbaie56435.2022.9985850","title":"Microsoft Malware Prediction Using LightGBM Model","year":2022,"lang":"en","type":"article","venue":"2022 3rd International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering (ICBAIE)","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Malware; Computer science; Artificial intelligence; Machine learning; Metric (unit); Heuristic; Feature (linguistics); Feature engineering; Data mining; Deep learning; Computer security; Engineering","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":[0.0005347071,0.001052429,0.0008302381,0.002594019,0.0004702913,0.001123514,0.001151086,0.001350458,0.003288647],"category_scores_gemma":[0.001390179,0.0003551278,0.001156051,0.0008810246,0.0002976348,0.0009399591,0.0005541019,0.001074742,0.001206596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001222257,"about_ca_system_score_gemma":0.001108586,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03033518,"about_ca_topic_score_gemma":0.02017104,"domain_scores_codex":[0.9997401,0.00003347923,0.00001271902,0.0000800168,0.00006132293,0.00007234998],"domain_scores_gemma":[0.9995633,0.0001858022,0.00005210282,0.00002344815,0.0001332307,0.00004214131],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005851337,0.0003743579,0.02656268,0.0001662092,0.0001626903,0.0003169608,0.00008484139,0.781952,0.001962459,0.003153625,0.01554125,0.1691377],"study_design_scores_gemma":[0.000005137528,0.00001316199,0.0006207065,0.000007233547,0.000008163964,0.00001570012,0.000005588352,0.9981835,0.0001956989,0.0006372309,0.0003039569,0.000003889626],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7060289,0.005005974,0.2565235,0.003752075,0.0006590657,0.0002756672,0.005211849,0.00829705,0.01424571],"genre_scores_gemma":[0.9465665,0.0007390819,0.04025602,0.0004160866,0.000140223,0.0001693697,0.003525136,0.000133914,0.008053582],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03033518,"threshold_uncertainty_score":0.06031722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1502154506320312,"score_gpt":0.3035154548151475,"score_spread":0.1533000041831163,"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."}}