A data scientist is tasked with building a machine learning model to predict customer churn for an e-commerce platform using Amazon SageMaker. The dataset contains various features, including customer demographics, purchase history, and engagement metrics. The data scientist decides to use a built-in algorithm provided by SageMaker for this task. After training the model, they evaluate its performance using a confusion matrix, which reveals that the model has a precision of 0.85 and a recall of 0.75. If the total number of positive cases in the dataset is 200, how many true positives did the model identify?