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Equation 38 · Part 7 · AI Feeds on the Distance Between an Intention and an Outcome

Symbol d_t

logit⁡Pr⁡(Yimtr=1)=β0+αm+β1qtr+β2dt+β3log⁡(1+ht)+urepo(t)+ut.\operatorname{logit}\Pr(Y_{imtr}=1)= \beta_0+\alpha_m+\beta_1 q_{tr}+\beta_2 d_t+ \beta_3\log(1+h_t)+u_{\mathrm{repo}(t)}+u_t.
dtd_t

What this part means

dtd_t is one of the signed contributions combined to compute the quantity on the left.

Its job in the formula

dtd_t is one of the signed contributions combined to compute the quantity on the left.

The passage around this formula

…logit⁡Pr⁡(Yimtr=1)=β0+αm+β1qtr+β2dt+β3log⁡(1+ht)+urepo(t)+ut\operatorname{logit}\Pr(Y_{imtr}=1)= \beta_0+\alpha_m+\beta_1 q_{tr}+\beta_2 d_t+ \beta_3\log(1+h_t)+u_{\mathrm{repo}(t)}+u_t. Here qtrq_{tr} is supplied input-context length in tokens, not tokens consumed after the agent has begun acting; using post-attempt expenditure would contaminate the predictor with behavior. The term dtd_t is a predeclared ordinary benchmark-difficulty score based only on endpoint-side, redaction-invariant features such as repository size band, static dependency reach, test-suite scope, and selected task-family label. It is deliberately conventional and admittedly imperfect. The terms…

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A subscript is a label attached below a symbol. It often selects a time step, component, category, or member of a sequence.

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