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 "text": "Data-Driven Agent-based Modeling of Innovation Diffusion presents the following source proposition: Our first step is to learn a model of individual agent behavior from individual adoption characteristics. This proposition is pertinent to Kaal's source-bound claim that The rapid adoption of deep learning and predictive analytics in law was driven by two enabling conditions: the increasing availability of digitized legal data and the computational power to process it. The proposed response is an extension: the relationship should remain limited to the retrieved source proposition and the mapped Kaal claim unless fuller source review supports a broader conclusion.",
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  "Mapping review tier: moderate-confidence claim review.",
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  "The source-to-claim mapping remains explicitly ambiguous and is published with that limitation."
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  "url": "https://doi.org/10.65109/uuxw5896"
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