We participated in two subtasks: Subtask 1, focusing on news articles, and Subtask 2, focusing on academic abstracts. Our submission is based on three distinct architectural approaches: (1) Fine-tuning a RoBERTa-base model, (2) A TF-IDF based system with a Linear Support Vector Machine (SVM) classifier, and (3) An experimental system named Candace, which leverages probabilistic features extracted from multiple Llama-3.2 models (1B and 3B variants) fed into a Transformer Encoder-based classifier. Our RoBERTa-based system demonstrated strong performance on the development and test sets for both subtasks and was chosen as our primary submission to both the shared subtasks.