Deductive entailment of reliability from shared epistemic properties

Determine whether associationism, atheoreticity, and opacity deductively entail the reliability of randomized controlled trials or analogous reliability-establishing processes in clinical translation.

Background

The paper examines whether the methodological standards used in clinical translation can be transferred to the construction and evaluation of machine-learning systems through a generative analogy. Clinical translation and machine learning are characterized by associationism, atheoreticity, and opacity, while randomized controlled trials and related practices are presented as mechanisms for managing the risks associated with those properties.

The authors explicitly distinguish empirical evidence that randomized controlled trials can manage these risks from a stronger deductive claim that the three epistemic properties logically entail reliability. The text leaves that entailment unresolved and consequently treats the transfer from medicine to machine learning as an assumption about likely effectiveness rather than as a deductive prediction.