{"id":"W3167387776","doi":"10.1109/tse.2021.3083715","title":"LogAssist: Assisting Log Analysis Through Log Summarization","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Software Engineering","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; Concordia University","funders":"","keywords":"Computer science; Automatic summarization; Workflow; Debugging; Event (particle physics); Information retrieval; Data mining; Programming language; Database","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":[0.0002293945,0.0002657026,0.000375182,0.0002541901,0.0002739386,0.0001592008,0.0003708436,0.0001669592,0.00005637623],"category_scores_gemma":[0.00008961248,0.0002524587,0.0003476823,0.002554681,0.00002250978,0.000670776,0.000007606499,0.0003288971,0.00005250273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000179298,"about_ca_system_score_gemma":0.0001060152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003157815,"about_ca_topic_score_gemma":0.00002295595,"domain_scores_codex":[0.9981899,0.00005463345,0.0004118876,0.0006033161,0.0003673632,0.0003729255],"domain_scores_gemma":[0.9984536,0.0003210868,0.0000808037,0.0008434422,0.0002028248,0.00009829106],"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":[0.000003971909,0.0001339214,0.004149628,0.0001129667,0.0004642459,0.00004133524,0.0003848039,0.9795771,0.0003145974,0.0002398325,0.00006664304,0.01451098],"study_design_scores_gemma":[0.001187579,0.0001551963,0.0298125,0.0003290111,0.0009138876,0.0001342684,0.00009854229,0.8839656,0.07611509,0.000164482,0.005398187,0.001725624],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008568943,0.0001083462,0.9884439,0.00008702269,0.001543952,0.00009990248,0.00001347401,0.001069241,0.00006528049],"genre_scores_gemma":[0.8385032,0.00003398417,0.1609939,0.0001162346,0.00006300619,0.00003817664,0.00001146729,0.00002183375,0.0002181691],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8299342,"threshold_uncertainty_score":0.9999928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01345450514441997,"score_gpt":0.230172734419048,"score_spread":0.2167182292746281,"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."}}