{"id":"W3175932722","doi":"10.1109/msr52588.2021.00028","title":"On the Naturalness and Localness of Software Logs","year":2021,"lang":"en","type":"article","venue":"","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Naturalness; Computer science; Software; State (computer science); Anomaly detection; Software system; Volume (thermodynamics); Data mining; Software engineering; Programming language","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":[],"consensus_categories":[],"category_scores_codex":[0.0002268239,0.00006552785,0.000108426,0.00001648863,0.00008079913,0.00003657093,0.0002989958,0.00004433635,0.0000317633],"category_scores_gemma":[0.0001536725,0.00003346406,0.00003314584,0.000244101,0.00006767951,0.0001256249,0.0001805331,0.00008553734,0.00001395959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008274593,"about_ca_system_score_gemma":0.0000530266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001506871,"about_ca_topic_score_gemma":0.000004548966,"domain_scores_codex":[0.9993502,0.00005359799,0.000127282,0.0001966741,0.0001679926,0.0001042423],"domain_scores_gemma":[0.9989208,0.0003913033,0.00003422902,0.0005061565,0.0001206785,0.00002682471],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00001552916,0.0002479298,0.07613393,0.0004732366,0.00006949368,0.00003188731,0.00187924,0.0001883204,0.0003412689,0.7196296,0.007687901,0.1933017],"study_design_scores_gemma":[0.002514055,0.0006028747,0.4109352,0.0008840455,0.00004024525,0.0004717413,0.001600002,0.03829459,0.3115931,0.2163511,0.01505275,0.001660295],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7610976,0.0003438045,0.2341781,0.002635465,0.0005404721,0.0001129476,0.000001152174,0.0001146921,0.0009758084],"genre_scores_gemma":[0.9965393,0.000008825008,0.002579947,0.0005386041,0.00001280974,0.000005254445,4.11578e-7,0.000002269435,0.0003125842],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5032785,"threshold_uncertainty_score":0.1364625,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00808648188254643,"score_gpt":0.2092436751128975,"score_spread":0.2011571932303511,"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."}}