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tokens: and our results not dominated by these corrections. This is discussed in more detail in Section 7 and Tables 2 and 3 . Table 2. Impact of the different corrections for observational systematic effects on the derived best-fitting bias b for the tomographic bins selected with our template method. The baseline mask is described in Section 4.2.3 and corresponds to all regions where our sample is complete (i.e. 10σ depth i ≥ 22.5). The third column corresponds to an additional masking of regions with high values of potential systematic variables such as seeing, where we observe large decrements in galaxy density (as described in Section 6.1 ). The fourth column refers to further corrections to w (θ) after these masks, in the cases where the data still correlate with maps for potential systematics (as discussed in Section 6.2 ). The fifth column reports the χ 2 /d.o.f. after all corrections applied. Empty entries refer to the cases where such corrections were not necessary. These values were obtained after fitting the ‘linear growth’ model for scales θ > θ min = (0.26, 0.18, 0.12, 0.08, 0.06) deg, from first to last z -bin. Table 3. Same as Table 2 but for the tomographic bins selected with the machine learning method. Different algorithms for photometric redshift estimation use different data quantities (most notably, template-based ones use magnitude errors while most machine learning do not). Thus, one expects a different response to potential systematics. 6.3 Stellar contamination Stellar contamination will affect the measured clustering signal, even if the cross-correlation between the galaxies and stars is negligible. This is due to the fact that rather than modulate the selection function of galaxies, stellar contamination introduces a separate population. In the limit where the stars are unclustered and the stellar contamination is constant, the observed galaxy density is δ o = (1 − f star )δ gal and thus i.e. the measured clustering is diluted by the square of the purity of the galaxy sample. We derive a general expression for the clustering of a galaxy population, given some stellar contamination (full details are shown in Appendix D ) where in this formalism, the number density of contaminating stars is allowed to be a function of not just the total density of stars, but also the survey observing conditions. The cross-correlation tests presented in the previous sections did not find stellar contamination to be a significant systematic contaminant. This suggests that the term in equation ( 26 ) proportional to w star, S is consistent with zero. However, the terms remain, and thus any stellar contamination must be accounted for. We estimate the stellar contamination in each photometric redshift bin by using DES observations in the COSMOS field. This region contains space-based observations which identify matching DES sources as point-like or not (as detailed in Section 4.1 ). Fig. 9 shows the purity of the DES sample in the COSMOS field