  We present $\texttt{Miko}$, a catalog-to-cosmology pipeline for general
flat-sky field-level inference, which provides access to cosmological
information beyond the two-point statistics. In the context of weak lensing, we
identify several new field-level analysis systematics (such as aliasing,
Fourier mode-coupling, and density-induced shape noise), quantify their impact
on cosmological constraints, and correct the biases to a percent level. Next,
we find that model misspecification can lead to both absolute bias and
incorrect uncertainty quantification for the inferred cosmological parameters
in realistic simulations. The Gaussian map prior infers unbiased cosmological
parameters, regardless of the true data distribution, but it yields
overconfident uncertainties. The log-normal map prior quantifies the
uncertainties accurately, although it requires careful calibration of the shift
parameters for unbiased cosmological parameters. We demonstrate systematics
control down to the $2\%$ level for both models, making them suitable for
ongoing weak lensing surveys.
