diff --git a/python/lsst/pipe/tasks/calibrateImage.py b/python/lsst/pipe/tasks/calibrateImage.py
index 4ba3dd492..3459b8cc1 100644
--- a/python/lsst/pipe/tasks/calibrateImage.py
+++ b/python/lsst/pipe/tasks/calibrateImage.py
@@ -392,6 +392,9 @@ def setDefaults(self):
         # Keep sky sources in the output catalog, even though they aren't
         # wanted for calibration.
         self.star_selector["science"].doSkySources = True
+        # Set the flux and error fields
+        self.star_selector["science"].signalToNoise.fluxField = "slot_CalibFlux_instFlux"
+        self.star_selector["science"].signalToNoise.errField = "slot_CalibFlux_instFluxErr"
 
         # Use the affine WCS fitter (assumes we have a good camera geometry).
         self.astrometry.wcsFitter.retarget(lsst.meas.astrom.FitAffineWcsTask)
diff --git a/tests/test_calibrateImage.py b/tests/test_calibrateImage.py
index 8522bd59f..c14a99cc4 100644
--- a/tests/test_calibrateImage.py
+++ b/tests/test_calibrateImage.py
@@ -189,7 +189,7 @@ def _check_run(self, calibrate, result, expect_calibrated_pixels: bool = True):
         self.assertEqual(result.stars["slot_PsfFlux_mag"].unit, u.ABmag)
 
         # Should have detected all S/N >= 10 sources plus 2 sky sources, whether 1 or 2 snaps.
-        self.assertEqual(len(result.stars), 7)
+        self.assertEqual(len(result.stars), 6)
         # Did the psf flags get propagated from the psf_stars catalog?
         self.assertEqual(result.stars["calib_psf_used"].sum(), 3)
 
@@ -319,7 +319,7 @@ def test_find_stars(self):
 
         # Only 5 psf-like sources with S/N>10 should be in the output catalog,
         # plus two sky sources.
-        self.assertEqual(len(stars), 7)
+        self.assertEqual(len(stars), 6)
         self.assertTrue(stars.isContiguous())
         # Sort in order of brightness, to easily compare with expected positions.
         stars.sort(stars.getPsfFluxSlot().getMeasKey())
@@ -420,8 +420,8 @@ def test_match_psf_stars(self):
         # sort() above leaves the catalog non-contiguous.
         stars = stars.copy(deep=True)
         np.testing.assert_array_equal(stars["calib_psf_candidate"],
-                                      [False, False, False, False, True, True, True])
-        np.testing.assert_array_equal(stars["calib_psf_used"], [False, False, False, False, True, True, True])
+                                      [False, False, False, True, True, True])
+        np.testing.assert_array_equal(stars["calib_psf_used"], [False, False, False, True, True, True])
         # Too few sources to reserve any in these tests.
         self.assertEqual(stars["calib_psf_reserved"].sum(), 0)