Artifacts for "Can Machine Learning Support the Selection of Studies for Systematic Literature Review Updates?". File used to answer RQ1: RQ1-RF-predictions.csv RQ1-RQ3-best-configuration-RF.csv File used to answer RQ2: RQ2-SVM-predictions.csv RQ2-best-configuration-SVM.csv File used to answer RQ3: RQ3-RF-normalized-predictions.csv RQ1-RQ3-best-configuration-RF.csv The file assessment-team-votes.csv contains the title of each study, a bolean indicating if it was included or not and the individual marks of each reviewer before applying the agreement criteria. The .bib files used in our experiment are available at: Our testing set: 'Testing set - Excluded.bib' (513 studies) and 'Testing set - Included.bib' (38 studies). All of the 551 studies we used, were obtained from the actual SLR Update Our training set: 'Training set - Excluded.bib' (83 studies - obtained by performing the backward snowballing using the Original SLR) and 'Training set - Included.bib' (45 studies - all studies that were included in the Original SLR). All of our code is available in the .zip file. Besides our pipeline, there's also some jupyter notebooks in code/analysis showing illustrating how we answered each of our questions.