{"id":"W4229000353","doi":"10.1145/3477314.3507053","title":"Fighting evil is not enough when refactoring metamodels","year":2022,"lang":"en","type":"article","venue":"Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing","topic":"Software Engineering Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Code refactoring; Correctness; Computer science; Context (archaeology); Quality (philosophy); Task (project management); Process (computing); Set (abstract data type); Domain (mathematical analysis); Metamodeling; Software engineering; Heuristic; Artificial intelligence; Programming language; Systems engineering; Engineering; 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":[0.008394767,0.00153045,0.001207996,0.001046864,0.0009647103,0.002862476,0.00155767,0.002185218,0.001645466],"category_scores_gemma":[0.03904507,0.0008801713,0.001121949,0.0007007231,0.0009059536,0.003965625,0.001975512,0.002038579,0.0008615646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006750096,"about_ca_system_score_gemma":0.00128653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001417492,"about_ca_topic_score_gemma":0.003095506,"domain_scores_codex":[0.9909739,0.004329413,0.0005129516,0.00110677,0.002716829,0.0003601515],"domain_scores_gemma":[0.9571003,0.0291844,0.003103737,0.007524389,0.002380739,0.0007064846],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.003053537,0.00185143,0.02784678,0.001722716,0.0006466602,0.00123001,0.004263402,0.09477236,0.2027251,0.007471398,0.008791816,0.6456249],"study_design_scores_gemma":[0.0005316737,0.003024996,0.02240648,0.0005316326,0.0006041444,0.002068281,0.003073086,0.7473341,0.1561663,0.03465644,0.02927376,0.0003292644],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5467642,0.001104936,0.4313313,0.002030905,0.0001319797,0.0003926156,0.0003121305,0.01285205,0.005080034],"genre_scores_gemma":[0.627458,0.000272121,0.3682057,0.0004563924,0.00002921731,0.0001154021,0.0005556602,0.001332532,0.001574932],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008394767,"threshold_uncertainty_score":0.04439628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0277705031316424,"score_gpt":0.2476717664792831,"score_spread":0.2199012633476407,"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."}}