I assure you, I am not basing my opinion from a Wikipedia intro, and haven't even looked at that wiki page.

A better metric for establishment of trust is scientific consensus, as scientists rarely just agree with one another without nitpicking unless there is overwhelming evidence from multiple sources converging on an emergent truth. Scientific consensus is important because often the statistical stringency used in studies has a fairly low threshold for statistical significance (p<0.05), which implies that if the experiments were flawless, the data has a 1/20 chance of reaching that significance threshold due to chance. If you have one paper that supports a hypothesis that has a 1/20 chance it was chance results, that's not the strongest evidence; however, if you have hundreds of papers meeting that statistical threshold it is now far lower than 1/20 that all of these papers and methods collectively are flawed and getting their results due to chance. This is the importance of consensus.

This is why I ask people to use multiple sources, if possible, to convey a message; there is a lower probability that the information is erroneous if there are multiple sources corroborating the same results and converging on the same conclusions with empirical backing.

Unfortunately, Mike Adams uses his own data points that frequently have selective information cherry picked to posture a compelling narrative, even if it means hacking his way to a statistically significant value (otherwise known as "p-hacking"). For more on data manipulation, and why science isn't broken, see this: https://fivethirtyeight.com/features/science-isnt-broken/#part1

That link comes with an interactive exercise where you can include, or omit data point to try and make compelling looking trends in data that would appear to "prove" a particular point, but that is "proven" by data manipulation and cherry picking. So, it is less likely that hundreds of studies were all flawed than just picking one and running with it (unless it was exceptionally scientifically rigorous).

Hope this clarifies a few things. It's a wild world out there, and I don't want to see people be unwittingly duped, as I have been before by these charlatans.

As a final note, another red flag is someones demand to appeal to emotion when their data cannot speak for itself. If someone needs to appeal to a perceived morality because their data is dodgy, than it might be that the entire argument is on a dodgy foundation, as the reasoning and rationale cannot stand on it's own without sensationalism. Scientists attempt to sensationalize their information as little as possible, as to keep it objective and as free from human/researcher bias. This is critical.