= Solution
Let $T_i>0$ be record time and let $x_i=(1,c_i,d_i)^T$ contain standardized climb and distance. Model 1 is the <normal linear model>
$$
T_i=x_i^T\beta+\varepsilon_i,
\qquad \varepsilon_i\overset{\mathrm{iid}}\sim N(0,\sigma^2).
$$
Model 2 applies the same model after a <logarithmic transformation>:
$$
\log T_i=x_i^T\alpha+e_i,
\qquad e_i\overset{\mathrm{iid}}\sim N(0,\tau^2),
$$
so $T_i$ is conditionally log-normal. Model 3 is a <Gamma regression with logarithmic link>:
$$
\mathbb E(T_i\mid x_i)=\mu_i,
\qquad
\operatorname{Var}(T_i\mid x_i)=\phi\mu_i^2,
\qquad
\log\mu_i=x_i^T\gamma.
$$
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