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Use conditional versus marginal posterior predictive checks to replicate new plates, rather than recycling the fitted plate effects. For each joint posterior draw of $(\alpha ,\beta ,\gamma ,\tau )$, draw fresh independent ${\lambda }_{ij}^{\mathrm{rep}}\sim N(0,{\tau }^2)$ and thenUse the same doses and three-plate design, giving the posterior predictive distribution for repeated experiments. Compare observed dose means and their trend, the high-dose downturn, within-dose spreads, and outliers with the replicated curves and intervals. For example compare a discrepancywith $T(y^{\mathrm{rep}};\psi )$ draw by draw. The resulting posterior predictive tail fraction or graphical rank assesses whether the observed trend is unusual under this model. Fresh plate effects are needed to assess the population dose-response assumption. Reusing the fitted effects would mainly check the conditional sampling layer and could hide systematic departures from the proposed curve.