{"id":"W4415500225","doi":"10.1007/s10115-025-02604-1","title":"X-HEART: eXplainable heterogeneous log anomaly detection using robust transformers","year":2025,"lang":"en","type":"article","venue":"Knowledge and Information Systems","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; IBM Canada; Vector Institute","keywords":"Interpretability; Anomaly detection; Raw data; Anomaly (physics); Transparency (behavior); Transformer","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008925922,0.001157927,0.0007513934,0.001388769,0.0003482746,0.001339356,0.002136327,0.0009370489,0.005546507],"category_scores_gemma":[0.004628624,0.0004862009,0.0008603664,0.0007106345,0.0006767585,0.00263236,0.002177854,0.001262952,0.001409006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003902235,"about_ca_system_score_gemma":0.0007902804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00214587,"about_ca_topic_score_gemma":0.002644699,"domain_scores_codex":[0.9994149,0.00008447211,0.00002786296,0.0002131705,0.0001990064,0.00006066031],"domain_scores_gemma":[0.9984416,0.0006866941,0.0001684469,0.0005004696,0.0001477691,0.0000549308],"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":[0.001488413,0.0002760544,0.01117442,0.0003325152,0.0002896667,0.001201502,0.0003512436,0.1471983,0.03414747,0.0414681,0.0227347,0.7393377],"study_design_scores_gemma":[0.00004899804,0.00006460985,0.0006267871,0.00001272299,0.00003435037,0.0001999647,0.00003159541,0.9498964,0.01071125,0.03535748,0.002994715,0.00002113623],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01030505,0.00006297203,0.9626764,0.00008981708,0.00003169617,0.00003812671,0.0004192946,0.02588117,0.0004954712],"genre_scores_gemma":[0.5035344,0.0001599632,0.4890385,0.0001452175,0.00007610048,0.00008672591,0.001629855,0.002312573,0.00301672],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005546507,"threshold_uncertainty_score":0.01855493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01243755298302605,"score_gpt":0.2372002165432896,"score_spread":0.2247626635602635,"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."}}