Digital models have become key sites of biological practice and science policy. This paper examines efforts to craft a digital salmon model for metabolic research. It traces the data configurations of feed, food, and health in Norway’s bioeconomy aspirations—from cell culture studies in the lab to an integrated digital repository and public health nutrition trials in schools. A response to policy calls for more sustainable aquaculture, digital models become lynchpins for intensified data sourcing. I describe how datafication and digital model integration enact a particular mode of management, focused on profitability and human preferences, when optimizing fish feed to sustainability goals. Integrating molecular biology and mathematical functions, digital modeling promotes the idea of a prediction machine for preemptive optimization of feed and food across settings. Yet, unforeseen disruptions to aquaculture, for instance, by algae and lice, expose the complexity of marine food webs and the limitations of digital models. Even while in the making, the digital fish model becomes performative and shapes knowledge practices much beyond the lab. As knowledge infrastructures, models participate in the remaking of metabolic relations, recalibrating decision-making, while feeding back into and co-shaping the very entities and environments they were crafted to investigate.

中文翻译：

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像模型鱼一样观察：数字提取如何调节代谢关系

数字模型已成为生物学实践和科学政策的关键场所。本文探讨了为代谢研究构建数字鲑鱼模型的努力。它追踪了挪威生物经济愿景中饲料、食品和健康的数据配置——从实验室的细胞培养研究到综合数字存储库和学校的公共卫生营养试验。为了响应更加可持续水产养殖的政策呼吁，数字模型成为强化数据采购的关键。我描述了在优化鱼饲料以实现可持续发展目标时，数据化和数字模型集成如何制定一种特定的管理模式，重点关注盈利能力和人类偏好。数字建模将分子生物学和数学函数相结合，促进了预测机的理念，用于跨环境对饲料和食品进行先发制人的优化。然而，藻类和虱子等对水产养殖造成的不可预见的破坏暴露了海洋食物网的复杂性和数字模型的局限性。即使在制作过程中，数字鱼模型也变得具有表演性，并且塑造了远远超出实验室的知识实践。作为知识基础设施，模型参与代谢关系的重建、重新校准决策，同时反馈并共同塑造它们所要研究的实体和环境。