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 →

Chris Gibson 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 5 5.00

Q All right. So tell us what recursion pharma, what kind of, what's your, your main product, your main focus, and what's your business model? How do you generate revenues?

A Yeah, absolutely. So what we're trying to do is shortcut the long, arduous, uh, path of getting, uh, drugs discovered into the market. Um, and so we do this by combining the best elements of biology, automation, and computation, uh, and doing drug discovery at scale across lots of diseases all in parallel. Uh, the business model initially has been to partner with large pharmaceutical companies who have drugs that they know a lot about, but ultimately did not end up making it to market. Um, so we've announced, for example, a partnership with Sanofi Genzyme, and in that particular case, we have drugs that, that, uh, they spent decades working on in many cases, and those drugs never ended up making it to patients, not because they're bad drugs, just because, uh, of a variety of business reasons, or even because the drug didn't show efficacy.

AI assessment note: “The business model initially has been to partner with large pharmaceutical companies”

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