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 →

Dave Burke no published score: only 1 usable exchange 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.

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1exchanges match
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Answered raw tape D 5 · C 5 · P 5 · Cm 5 5.00

Q So first in history opportunity for, um, scientists and entrepreneurs to go work on this dataset and create these virtual cell models. How do you tell the quality of one of these models?

A I mean, the, I mean, the core idea is it's what's its predictive ability, right? And so, you know, you, you take a cell, you perturb it, you can, you can do that either by, you know, from a genetic perspective, you can, you can suppress or, or, or, uh, upregulate genes and then, or, or apply drugs, and then you look at the response. And so the, the measure of the model is how well it predicts the, what we call the, the differentially expressed genes. Um, the, the reality is today the, the best models are, Um, very poor at this. Um, like the, the, the predictive ability of, of the DEGs as we call them is, is in the order of 10%. Um, and one of the conjectures.

AI assessment note: “the measure of the model is how well it predicts the, what we call the, the differentially expressed genes.”

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