{"id":"W2518214351","doi":"10.1145/2970276.2970348","title":"Migrating cascading style sheets to preprocessors by introducing mixins","year":2016,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Maintainability; Style sheet; Cascading Style Sheets; Programming language; Code (set theory); Preprocessor; Code reuse; Semantics (computer science); Software engineering; World Wide Web; XML; Web page; Software","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005278647,0.0001212257,0.0001153478,0.0001457674,0.00008987782,0.0001644788,0.000895761,0.00003855018,0.00007368053],"category_scores_gemma":[0.002305601,0.00008398772,0.00002929195,0.0005326483,0.00001344274,0.0004956972,0.0004281813,0.00008495279,0.0002140482],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000123054,"about_ca_system_score_gemma":0.00004063684,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007890126,"about_ca_topic_score_gemma":0.00001281723,"domain_scores_codex":[0.998382,0.00002634256,0.0001694116,0.0005904227,0.0003602951,0.0004715077],"domain_scores_gemma":[0.9983184,0.0007190052,0.00002328101,0.0006500905,0.0000876224,0.0002016235],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000007557162,0.00007702156,0.02689719,0.00007205414,0.00004397167,0.00002624788,0.006175471,0.0008863447,0.5288357,0.002428034,0.09670231,0.3378481],"study_design_scores_gemma":[0.0008839677,0.0003222488,0.0141595,0.0004090476,0.000004977243,0.00005799394,0.0001453726,0.0299084,0.9270393,0.0002743758,0.02557579,0.001219004],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2925676,0.0000424182,0.7037694,0.002478123,0.0001417736,0.0001082854,0.000001051605,0.0004968618,0.0003944726],"genre_scores_gemma":[0.9284242,0.000002250355,0.06833462,0.0001417946,0.00009004278,0.00002759531,2.313937e-7,0.0000158813,0.00296342],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6358565,"threshold_uncertainty_score":0.342492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009549300685594193,"score_gpt":0.2525183850635264,"score_spread":0.2429690843779322,"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."}}