The Exchanges

Every argument clarity score on this site is built from rows on this page. Each question and answer was assessed with names hidden, the host's own answers included, on four things from 1 to 5: directness (does it answer the question asked), coherence (do the ideas follow), precision (concrete details and clear references), compression (says a lot per word). The weighted mix (30/30/25/15) is the exchange score. A person's published score averages their exchange scores on raw tape only, at least 8 of them, shrunk toward the cohort mean. Full method →

Nils Mattisson no published score: no usable exchanges on raw tape, and a fair score needs 8+ record → ← everyone

Every exchange below was scored with names hidden, four dimensions each from 1 to 5. An exchange's score is 0.30·directness + 0.30·coherence + 0.25·precision + 0.15·compression. The published score averages the raw tape exchange scores and shrinks small samples toward the cohort mean, so five great answers can't beat twenty good ones. Produced feed rows count only toward coarse estimates, never toward a full score.

clear all ✕
1exchanges match
0on raw tape
0redirected or not addressed
Answered produced feed D 5 · C 5 · P 5 · Cm 4 4.85

Q How do you know that? I mean, break down how some of the algorithm works.

A So with the windows, for example, it's, it's, it's not so complicated. Like you can listen for the sound of breaking glass that has a very specific signature. So you can, in real time, I think you can hear that. And then you correlate it with the, uh, data from air pressure. So if you just drop, um, a water glass and it breaks, it might give off a similar kind of sound, but it won't change the air pressure, which a breaking window will. So when you have these things, uh, happening at the same time, you can be fairly certain that, that the window broke. Um, and similar with like, say your, your smoke detector would go off. Um, like that gives off a very distinct acoustic signature that, that it's fairly easy for us to, um, to, to detect.

AI assessment note: “you correlate it with the, uh, data from air pressure.”

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