{"id":"W7125651506","doi":"10.1109/cascon66301.2025.00032","title":"SynthLogAI: Generative AI for Synthetic Linux Log Generation and Evaluation","year":2025,"lang":"","type":"article","venue":"","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Brock University","funders":"","keywords":"Generative grammar; Generative model; Feature (linguistics); Field (mathematics); Set (abstract data type)","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":[0.002962131,0.0003410993,0.00042889,0.0002390161,0.0007537498,0.0005429662,0.0003897023,0.0003269747,0.00007665414],"category_scores_gemma":[0.0005801829,0.0002856802,0.0001424944,0.0005282462,0.0001902487,0.0007964836,0.0002297076,0.0001746671,0.00002973987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002635999,"about_ca_system_score_gemma":0.0009070083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006397448,"about_ca_topic_score_gemma":0.00007506289,"domain_scores_codex":[0.9967913,0.0004167552,0.0007616081,0.001147907,0.0004553996,0.000427003],"domain_scores_gemma":[0.9972573,0.0003176133,0.0001754184,0.0008443629,0.001300996,0.0001043366],"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":[0.00005773578,0.0002647187,0.002785759,0.0006562232,0.0002107925,8.037817e-7,0.00198817,0.006926673,0.002987,0.02798848,0.01075956,0.9453741],"study_design_scores_gemma":[0.0009180641,0.0002440309,0.001842535,0.000164037,0.0001391944,0.000005139226,0.0000664715,0.9743906,0.01592478,0.004157955,0.001839024,0.0003081312],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09209285,0.002724629,0.8902962,0.006646464,0.004206698,0.0027864,0.00001187258,0.0001014456,0.001133394],"genre_scores_gemma":[0.9789009,0.0002206235,0.01619256,0.001788264,0.0004368946,0.0005124787,0.00001742493,0.000011163,0.00191968],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.967464,"threshold_uncertainty_score":0.9999595,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0343974636271998,"score_gpt":0.3264284678149116,"score_spread":0.2920310041877118,"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."}}