{"id":"W4376606564","doi":"10.1109/saner56733.2023.00019","title":"Studying and Complementing the Use of Identifiers in Logs","year":2023,"lang":"en","type":"article","venue":"","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Dependency graph; Computer science; Identifier; Dependency (UML); Java; Data mining; Software; Source code; Call graph; Coding (social sciences); Process (computing); Graph; Static program analysis; Software development; Programming language; Software engineering; Theoretical computer science; Statistics","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":[0.000707786,0.00003549163,0.0000709445,0.0000626078,0.00006589709,0.00006127528,0.0002068291,0.00001154965,0.000002835094],"category_scores_gemma":[0.00004891502,0.00002107024,0.00001459525,0.0004568516,0.00003307536,0.0002704549,0.0002801537,0.00003889742,0.000008030744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006471135,"about_ca_system_score_gemma":0.000009339512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002761226,"about_ca_topic_score_gemma":0.0000653065,"domain_scores_codex":[0.999432,0.00004099371,0.0001727309,0.0001229192,0.0001168227,0.0001144974],"domain_scores_gemma":[0.9994847,0.0002130829,0.0000358824,0.0002326166,0.00002196062,0.00001171552],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000001068067,0.00001356531,0.973718,0.00005542163,0.000008679145,0.000002447636,0.003861643,0.0005203193,0.0001628086,0.002613733,0.001082642,0.01795964],"study_design_scores_gemma":[0.0002246439,0.00001773804,0.8824226,0.000036847,0.000001815478,0.000002059448,0.0009287621,0.1141515,0.0003105375,0.0005872241,0.001245883,0.00007044723],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9839394,0.00001269703,0.01532781,0.0003033255,0.0001505961,0.0001295324,2.583026e-7,0.00006532677,0.000071047],"genre_scores_gemma":[0.9982289,0.000008984549,0.001589273,0.00005019057,0.000005176763,0.000004918348,2.542881e-7,0.000001350799,0.0001109715],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1136312,"threshold_uncertainty_score":0.08592194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1456248949649242,"score_gpt":0.296689266394009,"score_spread":0.1510643714290848,"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."}}