Today, with modern search and computerized tools, one of the primary heuristics I use for determining which preprints to read is "do I know any of the authors".

Today, with modern search and computerized tools, one of the primary heuristics I use for determining which preprints to read is "do I know any of the authors". If I don't know you, your ideas are most likely not worth reading, even if they appear to be about a topic I'm interested in. There are so many papers published every year and so little time to read them properly, and the search tools that exist are not that good. If you don't have an established reputation, your best bet is submitting your work to a relevant journal or conference, where the peer reviewers will usually give you a fair chance. Google Scholar is a good example of how bad the tools are. Its recommendations are apparently based on things like the papers you publish, the papers you cite, and the papers that cite your work, which sounds superficially reasonable. That worked well enough when I was doing my PhD within the boundaries of an established academic field. But when I started doing more interdisciplinary work, the recommendations quickly turned into garbage. A better recommendation system would understand that there is a field I work in, an upstream field I take ideas from, a downstream field I contribute to, and several fields further downstream that use the work I contributed to.