There is a complex interplay between the models in dark matter detection experiments that have led to a difficulty in interpreting the results of the experiments and ascertain whether we have detected the particle or not. The aim of this paper is to categorise and explore the different models used in said experiments, by emphasizing the distinctions and dependencies among different types of models used in this field. With a background theory, models are categorised into four distinct types: background theory, theoretical, phenomenological, experimental and data. This taxonomy highlights how each model serves a unique purpose and operates under varying degrees of independence from their respective frameworks. A key focus is on the experimental model, which is shown to rely on constraints from both data and phenomenological ones. The article argues that while theoretical models provide a backdrop for understanding the nature of dark matter, the experimental models must stand independently, particularly in their methodological approaches. This is done via a discussion of the inherent challenges in dark matter detection, such as inconsistent results and difficulties in cross-comparison, stemming from the diverse modelling approaches.

暗物质探测实验中的模型之间存在复杂的相互作用，这导致难以解释实验结果并确定我们是否检测到了粒子。本文的目的是通过强调该领域中使用的不同类型模型之间的区别和依赖关系，对所述实验中使用的不同模型进行分类和探索。在背景理论中，模型分为四种不同的类型：背景理论、理论、现象学、实验和数据。此分类法强调了每个模型如何服务于独特的目的，并在不同程度的独立性下独立于其各自的框架。一个关键的重点是实验模型，它被证明依赖于数据和现象学的约束。文章认为，虽然理论模型为理解暗物质的本质提供了背景，但实验模型必须独立存在，尤其是在其方法论方法方面。这是通过讨论暗物质探测的固有挑战来完成的，例如源于不同建模方法的不一致结果和交叉比较的困难。