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A possible limitation of a model can be identified by examining its assumptions, data quality, and generalizability. For instance, if a model relies on outdated or biased data, it may produce inaccurate predictions, leading to poor decision-making. Additionally, if the model oversimplifies complex relationships, it might fail to capture critical nuances, making it less useful in real-world applications. Recognizing these limitations is essential for refining the model and ensuring its relevance and effectiveness.

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