{"id":"W1513330488","doi":"","title":"Applying data mining to software maintenance records","year":2003,"lang":"en","type":"article","venue":"Conference of the Centre for Advanced Studies on Collaborative Research","topic":"Software Engineering Research","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Software quality; Data mining; Software maintenance; Software; Quality (philosophy); Software system; Software engineering; Software development; Data science; 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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.002752461,0.000244967,0.0004254346,0.0002525784,0.0006097401,0.0001393095,0.003750544,0.0000573239,0.000005985015],"category_scores_gemma":[0.06840558,0.0001797347,0.00005532215,0.003128893,0.0003061734,0.0004085266,0.002038843,0.0003833291,0.00001526998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003288823,"about_ca_system_score_gemma":0.0008227712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002654178,"about_ca_topic_score_gemma":0.00007713015,"domain_scores_codex":[0.996112,0.0004817987,0.0003782843,0.0009595741,0.001122321,0.0009459967],"domain_scores_gemma":[0.983655,0.007498176,0.0001495246,0.002652841,0.005839549,0.0002049604],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001085223,0.0008158288,0.01244375,0.00164265,0.001180138,0.00004742617,0.03085585,0.01961843,0.0106605,0.3105809,0.2109913,0.400078],"study_design_scores_gemma":[0.005730109,0.002848621,0.001836494,0.005698403,0.00003570111,0.000009232131,0.05964921,0.01380518,0.1835491,0.0238445,0.7008216,0.002171827],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0689855,0.00464158,0.8735063,0.02185799,0.006044297,0.02074758,0.001150629,0.0006309061,0.002435195],"genre_scores_gemma":[0.6117616,0.0004300541,0.3801921,0.0001437868,0.00006651406,0.001709877,0.000008031288,0.00006111801,0.005626904],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5427761,"threshold_uncertainty_score":0.9394416,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1793986325428564,"score_gpt":0.4154253981500171,"score_spread":0.2360267656071606,"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."}}