I like that HowTruthful uses the idea of (independent) hierarchical subarguments, since I had the same idea. Have you been able to persuade very many to pay for it?

My first thought about it was that the true/false scale should have two dimensions, knowledge & probability:

One of the many things I wanted to do on my site was to gather user opinions, and this does that. ✔ I think of opinions as valuable evidence, just not always valuable evidence about the question under discussion (though to the extent people with "high knowledge" really have high knowledge rather than pretending to, it actually is evidence). Incidentally I think it would be interesting to show it as a pyramid but let people choose points outside the pyramid, so users can express their complete certainty about matters they have little knowledge of...

Here are some additional thoughts about how I might enhance HowTruthful if it were my project:

(1) I take it that the statements form a tree? I propose that statements should form a DAG (directed acyclic graph ― a cyclic graph could possibly be useful, but would open a big can of worms). The answer to one question can be relevant to many others.

(2) Especially on political matters, a question/statement can be contested in various ways:

• "ambiguous/depends/conflated/confused": especially if the answer depends on the meaning of the question; this contestation can be divided into just registering a complaint, on the one hand, and proposing a rewording or that it be split into clearer subquestions, on the other hand. Note that if a question is split, the original question can reasonably keep its own page so that when someone finds the question again, they are asked which clarified question they are interested in. If a question is reworded, potentially the same thing can be done, with the original question kept with the possibility of splitting off other meanings in the future.
• "mu": reject the premise of the question (e.g. "has he stopped beating his wife?"), with optional explanation. Also "biased" (the question proposes its own answer), "inflammatory" (unnecessarily politicized language choice), "dog whistle" (special case of politicized language choice). Again one can imagine a UI to propose rewordings. 
• sensitive (violence/nudity): especially if pic/vid support is added, some content can be simultaneously informative/useful and censored by default
• spam (irrelevant and inappropriate => deleted), or copyright claim (deleted by law)

(3) The relationship between parent and child statements can be contested, or vary in strength:

• "irrelevant/tangential": the statement has no bearing on its parent. This is like a third category apart from pro/evidence in favor and con/evidence against.
• "miscategorized": this claims that "pro" information should be considered "con" and vice versa. Theoretically, Bayes' rule is useful for deciding which is which.

This could be refined into a second pyramid representing the relationship between the parent and child statements. The Y axis of the pyramid is how relevant the child statement is to the parent, i.e. how correlated the answers to the two questions ought to be. The X axis is pro/con (how the answer to the question affects the answer to the parent question.) Note that this relationship itself could reasonably be a separate subject of debate, displayable on its own page.

(4) Multiple substatements can be combined, possibly with help from an LLM. e.g. user pastes three sources that all make similar points, then the user can select the three statements and click "combine" to LLM-generate a new statement that summarizes whatever the three statements have in common, so that now the three statements are children of the newly generated statement.

(5) I'd like to see automatic calculation of the "truthiness" of parent statements. This offers a lot of value in the form of recursion: if a child statement is disproven, that affects its parent statement, which affects the parent's parent, etc., so that users can get an idea of the likelihood of the parent statement based on how the debate around the great-grandchild statements turned out. Related to that, the answers to two subquestions can be highly correlated with each other, which can decrease the strength of the two points together. For example, suppose I cite two sources that say basically the same thing, but it turns out they're both based on the same study. Then the two sources and the study itself are nearly 100% correlated and can be treated altogether as a single piece of evidence. What UI should be used in relation to this? I have no idea.

(6) Highlighting one-sentence bullet points seems attractive, but I also think Fine Print will be necessary in real-life cases. Users could indicate the beginning of fine print by typing one or two newlines; also the top statement should probably be cut off (expandable) if it is more than four lines or so.

(7) I propose distinguishing evidentiary statements, which are usually but not always leaf nodes in the graph. Whenever you want to link to a source, its associated statement must be a relevant summary, which means that it summarizes information from that source relevant to the current question. Potentially, people can just paste links to make an LLM generate a proposed summary. Example: if the parent statement proposes "Crime rose in Canada in 2022", and in a blank child statement box the user pastes a link to "The root cause': Canada outlines national action plan to fight auto theft", an LLM generates a summary by quoting the article: "According to 2022 industry estimates [...], rates of auto theft had spiked in several provinces compared to the year before. [Fine print] In Quebec, thefts rose by 50 per cent. In Ontario, they were up 34.5 per cent."

(8) Other valuable features would include images, charts, related questions, broader/parent topics, reputation systems, alternative epistemic algorithms...

(9) Some questions need numerical (bounded or unbounded) or qualitative answers; I haven't thought much about those. Edit: wait, I just remembered my idea of "paradigms", i.e. if there are appropriate answers besides "yes/true" and "false/no", these can be expressed as a statement called a "paradigm", and each substatement or piece of available evidence can (and should) be evaluated separately against each paradigm. Example: "What explains the result of the Michelson–Morley experiment of 1881?" Answer: "The theory of Special Relativity". Example: "What is the shape of the Earth?" => "Earth is a sphere", "Earth is an irregularly shaped ellipsoid that is nearly a sphere", "Earth is a flat disc with the North Pole in the center and Antarctica along the edges". In this case users might first place substatements under the paradigm that they match best, but then somehow a process is needed to consider each piece of evidence in the context of each subparadigm. It could also be the case that a substatement doesn't fit any of the current paradigms well. I was thinking that denials are not paradigms, e.g. "What is the main cause of modern global warming?" can be answered with "Volcanoes are..." or "Natural internal variability and increasing solar activity are..." but "Humans are not the cause" doesn't work as an answer ("Nonhumans are..." sounds like it works, but allows that maybe elephants did it). "It is unknown" seems like a special case where, if available evidence is a poor fit to all paradigms, maybe the algorithm can detect that and bring it to users' attention automatically?

Another thing I thought a little bit about was negative/universal statements, e.g. "no country has ever achieved X without doing Y first" (e.g. as evidence that we should do Y to help achieve X). Statements like this are not provable, only disproveable, but it seems like the more people who visit and agree with a statement, without it being disproven, the more likely it is that the statement is true... this may impact epistemic algorithms somehow. I note that when a negative statement is disproven, a replacement can often be offered that is still true, e.g. "only one country has ever achieved X without doing Y first".

(10) LLMs can do various other tasks, like help detect suspicious statements (spam, inflammatory language, etc.), propose child statements, etc. Also there could be a button for sending statements to (AI and conventional) search engines...