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I'll present a series of numerical experiments to test simple analytical predictions for large-scale Lyman-alpha forest bias parameters. Despite relying on second-order SPT, some of the predictions are surprisingly accurate, especially if thermal broadening is not taken into account. I'll also discuss details of using filtered and squared small-scale fields as robust tracers of large-scale structure that might be useful for non-Gaussianity measurements.