{"id":"W2105672266","doi":"10.1145/1852786.1852792","title":"Understanding the impact of code and process metrics on post-release defects","year":2010,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":94,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Merge (version control); Software quality; Software metric; Data mining; Eclipse; Source code; Process (computing); Software; Data science; Machine learning; Software development; Information retrieval; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007652773,0.001559706,0.00069335,0.004579549,0.0003036452,0.001698239,0.0008831182,0.001640958,0.001309283],"category_scores_gemma":[0.08255118,0.0006946943,0.001281684,0.002191256,0.000690972,0.003698243,0.0009701687,0.001715075,0.0004290849],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000930841,"about_ca_system_score_gemma":0.001094017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008818725,"about_ca_topic_score_gemma":0.01081598,"domain_scores_codex":[0.9954495,0.002068695,0.0002319761,0.0007966507,0.001127873,0.0003252099],"domain_scores_gemma":[0.8319849,0.1372962,0.01664263,0.006741744,0.006333252,0.001001257],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000463673,0.0005358935,0.5969118,0.0002180289,0.000492317,0.0004979184,0.0007937077,0.2811986,0.005860043,0.004282796,0.000984517,0.1077607],"study_design_scores_gemma":[0.00001426196,0.0003035866,0.175212,0.00002954978,0.0001084227,0.0001630236,0.0001456624,0.8164179,0.002653258,0.00446139,0.0004503231,0.00004064443],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8797784,0.000415404,0.1162219,0.0006058105,0.00002368975,0.00007674016,0.0005047511,0.0007938434,0.001579424],"genre_scores_gemma":[0.9897559,0.0001450403,0.009215545,0.0000259815,0.00001258813,0.00002662972,0.0004251801,0.00006298564,0.0003301531],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008818725,"threshold_uncertainty_score":0.04047221,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0564791787515353,"score_gpt":0.3251365449346347,"score_spread":0.2686573661830994,"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."}}