Evaluating an LLM Ensemble Strategy

A research team aims to build an ensemble of language models to improve performance on a complex question-answering task. Their proposed strategy is to take a single, large pre-trained model and fine-tune it ten separate times on the exact same dataset, using different random seeds for each training run. They believe the inherent randomness in the training process will create a sufficiently diverse set of models. Which of the following statements provides the most accurate critique of this strategy?

A data science team is building an ensemble of Large Language Models to improve performance on a sentiment analysis task. Match each proposed strategy with the primary method of achieving model diversity it represents.