Not all transit fits yield mid-transit time estimates that are equally informative. In particular, low signal-to-noise transits may produce posterior distributions that appear well behaved despite being dominated by the imposed priors or by chance alignment with noise. To distinguish genuinely informative timing constraints from such cases, we classify each transit fit based on the structure of its posterior distribution and the degree to which the transit model is preferred to a flat, no-transit model. Our classification scheme proceeds hierarchically, and each transit is assigned to one of four mutually exclusive classes, as described below.

4.4.1 Prior-limited Fits are classified as prior-limited when the posterior distribution of the mid-transit time 𝑡0 is strongly influenced by the bounds of the uniform timing prior. Specifically, if the posterior median is consistent with the lower or upper prior boundary to within three times the lower or upper timing uncertainty, respectively, the timing constraint is considered prior-dominated and the transit is assigned to this class. This criterion captures cases where the apparent constraint arises primarily from the imposed timing window rather than from information in the data and is often associated with a mid-transit timing error (extracted minus injected time) much smaller than the calculated timing uncertainty.
4.4.2 Low significance For fits that are not prior-limited, we assess whether the data provide meaningful support for a transit-shaped signal within the transit window. This is quantified using the difference in maximum log-likelihood, Δ ln L, between the transit model and a null (constant-flux) model. In the null model, we fix the jitter term to the best-estimate value from the transit model fit. This prevents highlikelihood null model fits from being achieved through unrealistic inflation of per-point uncertainties, which can consume the significance of the transit model relative to the null model. Transits with Δ ln L < 5 are classified as low significance, indicating that the transit model is not strongly preferred over noise within the fitted window.
4.4.3 Asymmetric high significance and symmetric high significance Transits with Δ ln L ≥5 are considered to have significant support for a transit-shaped signal. Among these, we further distinguish cases based on the symmetry of the marginal posterior distribution of 𝑡0. To quantify this, we define an asymmetry metric based on posterior quantiles, 𝐴= 𝑞84 + 𝑞16 −2𝑞50
𝑞84 −𝑞16 , (3) where 𝑞16, 𝑞50, and 𝑞84 denote the 16th, 50th, and 84th percentiles of the posterior, respectively. This quantity provides a measure of skewness in the interval [−1, 1]. Transits with |𝐴| > 0.3 are classified as asymmetric high significance, typically corresponding to cases where the timing constraint is strongly one-sided or multi-modal. Transits with |𝐴| ≤0.3 are classified as symmetric high significance and represent the most robust per-transit timing measurements, exhibiting approximately unimodal and symmetric posterior distributions for 𝑡0. This classification forms the basis for the population-level analysis of transit timing performance presented in the following section.