They’re not saying that. How did you summarize 23 words using 39 words, and get the summary wrong?
They’re saying that there is no external professional vouching for MBFC’s conclusions, which is their usual gold standard for things being “reliable.” And that, on top of that, people within Wikipedia have specifically pointed out flaws with how MBFC does things, without any of the qualifications and categories that you added.
I’m trying to summarize the wiki reasoning/what’s in the wiki page about mbfc criticisms
Got it, that does make sense. You should know, though, that Wikipedia on the content side is a different thing from Wikipedia on the talk page side.
People can have nice things to say about a source in their Wikipedia page about the source, on the content side, while there’s still a consensus on the talk page side that the source is unreliable and shouldn’t be used for sourcing claims about other matters on other Wikipedia pages. The big table that I and someone else linked to are good summaries of the consensus on the talk page side, which is what’s most relevant here.
A 2018 year-in-review and prospective on fact-checking from the Poynter Institute (which develops PolitiFact[27]) noted a proliferation of credibility score projects, including Media/Bias Fact Check, writing that “While these projects are, in theory, a good addition to the efforts combating misinformation, they have the potential to misfire,” and stating that “Media Bias/Fact Check is a widely cited source for news stories and even studies about misinformation, despite the fact that its method is in no way scientific.”[6] Also in 2018, a writer in the Columbia Journalism Review described Media Bias/Fact Check as “an armchair media analysis”[28] and characterized their assessments as “subjective assessments [that] leave room for human biases, or even simple inconsistencies, to creep in”.[29] A study published in Scientific Reports wrote: “While [Media Bias/Fact Check’s] credibility is sometimes questioned, it has been regarded as accurate enough to be used as ground-truth for e.g. media bias classifiers, fake news studies, and automatic fact-checking systems.”[19]