{"id":"W3106278391","doi":"10.1109/issrew.2016.43","title":"On Automatic Detection of Performance Bugs","year":2016,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Software bug; Operating system; Software","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003159309,0.001447764,0.0007667461,0.006065819,0.0006305026,0.001292655,0.001504964,0.001557117,0.001147042],"category_scores_gemma":[0.02899262,0.0004613267,0.000695827,0.002322158,0.0005155479,0.002285028,0.001173953,0.001075231,0.001400555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008487643,"about_ca_system_score_gemma":0.001627667,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009182759,"about_ca_topic_score_gemma":0.01019474,"domain_scores_codex":[0.9945524,0.001205898,0.000481687,0.001374088,0.002091864,0.000293985],"domain_scores_gemma":[0.9629058,0.02037023,0.006822374,0.002506436,0.006802571,0.0005926586],"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":[0.0005357059,0.0008077509,0.3148804,0.0007540825,0.0002096762,0.0007185257,0.0004659227,0.04311175,0.01584266,0.001791038,0.01571772,0.6051648],"study_design_scores_gemma":[0.00004888092,0.0003630151,0.0587319,0.000134936,0.0001029009,0.00116152,0.0001878048,0.9174497,0.01467807,0.003464977,0.003608184,0.00006801514],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5190006,0.002815426,0.4444247,0.00110996,0.000284787,0.0004167678,0.003680344,0.02358168,0.004685717],"genre_scores_gemma":[0.8724393,0.0004549491,0.1205087,0.0002032283,0.00009276967,0.0001070577,0.003860439,0.0002353241,0.002098212],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009182759,"threshold_uncertainty_score":0.01825863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01032488581947326,"score_gpt":0.2321164308094904,"score_spread":0.2217915449900172,"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."}}