{"id":"W3004224429","doi":"10.1145/3381343.3381345","title":"Big data driven genetic improvement for maintenance of legacy software systems","year":2020,"lang":"en","type":"article","venue":"ACM SIGEVOlution","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Engineering and Physical Sciences Research Council","keywords":"Software; Conversation; Artificial intelligence; Computer science; Library science; Sociology; Operating system","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001159655,0.000104939,0.0001458425,0.00003333226,0.000127745,0.00005031985,0.001956836,0.00004537983,0.000001354367],"category_scores_gemma":[0.0002467863,0.0001019302,0.000044892,0.0003016432,0.00004202375,0.0004483389,0.0007955964,0.00005966315,0.00001559793],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005254613,"about_ca_system_score_gemma":0.0001180172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000076806,"about_ca_topic_score_gemma":0.000003188258,"domain_scores_codex":[0.998776,0.00002018528,0.0003083443,0.0004800351,0.0001985795,0.0002168113],"domain_scores_gemma":[0.9981141,0.00009579973,0.0001749936,0.001369437,0.0001731217,0.00007251642],"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":[0.00007132597,0.0007659588,0.004262615,0.001095605,0.0002624586,0.00000794489,0.001341627,0.04700141,0.05479728,0.1807236,0.1119121,0.5977581],"study_design_scores_gemma":[0.0004939345,0.0002489753,0.007139458,0.00003358861,0.00001902072,0.000003503138,0.00006296474,0.9544515,0.0003132385,0.002429229,0.03461402,0.0001905691],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004983799,0.0006724445,0.990714,0.002429607,0.0003342971,0.0006073048,0.0001298193,0.0001135923,0.00001516778],"genre_scores_gemma":[0.7421415,0.00004410974,0.2570434,0.0001658724,0.0002980947,0.0001398873,0.00009814293,0.00001019341,0.00005874618],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9074501,"threshold_uncertainty_score":0.4156595,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06133430161237951,"score_gpt":0.263458571486809,"score_spread":0.2021242698744295,"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."}}