{"id":"W2017671454","doi":"10.1109/fosm.2008.4659256","title":"The past, present, and future of software evolution","year":2008,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":128,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria; University of Waterloo","funders":"","keywords":"Software evolution; Software development; Computer science; Software analytics; Social software engineering; Software; Software engineering; Software system; Software maintenance; Software construction; 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":[],"consensus_categories":[],"category_scores_codex":[0.0001176128,0.00004424995,0.00004651634,0.00003368589,0.0001178252,0.0000205061,0.0003685803,0.00002484128,0.000002938451],"category_scores_gemma":[0.00004884038,0.00002782616,0.00001663217,0.0002059672,0.00006225064,0.0001322877,0.0001834074,0.0000675501,0.000005036568],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001359958,"about_ca_system_score_gemma":0.00002995296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002000808,"about_ca_topic_score_gemma":8.042691e-7,"domain_scores_codex":[0.999432,0.0000183966,0.00007109169,0.0001171543,0.0002221323,0.0001391942],"domain_scores_gemma":[0.9991601,0.0003966702,0.00001472148,0.0003204831,0.00006672912,0.00004128788],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001590262,0.00008346474,0.4931644,0.00008339063,0.00005723029,0.00003276167,0.001396374,0.0003897088,0.0003538527,0.07234967,0.1586436,0.2734296],"study_design_scores_gemma":[0.0002218604,0.00007501751,0.9108018,0.000005643076,0.000001265896,0.00008565473,0.00002779284,0.00883831,0.0005120862,0.00142025,0.07789505,0.0001152818],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05451,0.002048113,0.9394218,0.003106254,0.000265187,0.0001237847,6.351171e-7,0.0002544527,0.000269718],"genre_scores_gemma":[0.9423518,0.0002515937,0.05483461,0.00001976122,0.000745707,0.00001423076,4.053848e-7,0.000008812432,0.001773081],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8878418,"threshold_uncertainty_score":0.1134718,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01236962622403282,"score_gpt":0.2343688758300921,"score_spread":0.2219992496060592,"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."}}