{"id":"W1560640562","doi":"10.1007/978-3-540-28633-2_41","title":"Using Evolutionary Learning of Behavior to Find Weaknesses in Operating Systems","year":2004,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Artificial Immune Systems Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Randomness; Strengths and weaknesses; Reboot; Hacker; Process (computing); Creativity; Software engineering; Software; Simple (philosophy); 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002958749,0.0002370893,0.000361977,0.0005795443,0.0001160839,0.00007303023,0.0004412463,0.000171633,0.000008125157],"category_scores_gemma":[0.0000457608,0.0002595148,0.00003817564,0.000451755,0.0001345427,0.0001496548,0.0001790446,0.0004459322,0.00001120714],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005636203,"about_ca_system_score_gemma":0.0002088278,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003695272,"about_ca_topic_score_gemma":0.00006523682,"domain_scores_codex":[0.9984239,0.0000145479,0.0005546227,0.0004017297,0.0003203141,0.0002848712],"domain_scores_gemma":[0.9992867,0.0001052193,0.00009643967,0.0003467533,0.0001141171,0.00005075535],"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":[4.452641e-7,0.000006641648,0.0002880438,0.00007464107,0.000002445074,0.000006152356,0.0005147707,0.9724326,0.01612083,0.001010226,5.077513e-7,0.009542744],"study_design_scores_gemma":[0.0001038038,0.00004384123,0.001345607,0.002206525,0.00001058832,0.00003963606,0.000004323171,0.9918365,0.002958124,0.0007976066,0.000163313,0.0004900568],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0261025,0.0007533917,0.9711013,0.00001284285,0.0007119157,0.0006364211,0.00000479523,0.0000790316,0.000597838],"genre_scores_gemma":[0.9452416,0.000004358159,0.05447599,0.000007852161,0.0001549966,0.00003099745,0.000003134695,0.00003895269,0.00004215883],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9191391,"threshold_uncertainty_score":0.9999857,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02660751745161068,"score_gpt":0.265059100459082,"score_spread":0.2384515830074713,"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."}}