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Equation 11 · Part 6 · How to Evaluate Codex Beyond SWE-bench and Vendor Scores

Symbol N

logit⁡(pir)=α+ur+β⊤xir,ur∼N(0,σr2),\operatorname{logit}(p_{ir})=\alpha+u_r+\beta^\top x_{ir}, \qquad u_r\sim\mathcal N(0,\sigma_r^2),
NN

What this part means

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

Its job in the formula

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

The passage around this formula

A hierarchical model can represent repository effects: logit⁡(pir)=α+ur+β⊤xir,ur∼N(0,σr2)\operatorname{logit}(p_{ir})=\alpha+u_r+\beta^\top x_{ir}, \qquad u_r\sim\mathcal N(0,\sigma_r^2). where r indexes repositories and xirx_{ir} task characteristics. The estimate can then expose between-repository variance rather than hiding it inside a global mean. Bootstrap intervals should resample at relevant task-family or repository levels when generalization across those units is the target.

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Learn the underlying idea

A function assigns an output to each allowed input. The expression f(x) means “apply f to x”.

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See this notation across published equations →

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