Recent work in Bayesian, agent-based modelling of scientific communities has employed the Bala-Goyal framework to study the mechanisms involved when industry influence applies the so-called 'Tobacco Strategy' to undermine collective inquiry. Motivated by limitations of these models, we propose an alternative based on a recently introduced framework for normative argument exchange across networks. We implement representations of two distinct types of industry influence: Obfuscating' influence directs inquiry to experiments with low expected value of information.Misleading' influence filters private research and only communicates misleading signals from the world. We explored the impacts of both strategies on the polarization \& mean error of, and flow of information through, social networks of scientists via computer simulations. We conclude that even against highly optimistic background assumptions, and in a less simplified model of inquiry and argumentation, industry influence poses a plausible threat to collective deliberation.