diff --git a/config/calibration/mask_v1.X.10.yaml b/config/calibration/mask_v1.X.10.yaml
index 4729bfdc..9118bd93 100644
--- a/config/calibration/mask_v1.X.10.yaml
+++ b/config/calibration/mask_v1.X.10.yaml
@@ -1,5 +1,5 @@
 # Config file for masking and calibration.
-# Standard cuts without halo masks, type v1.X.10
+# Standard cuts without halo masks, including deblended objects, type v1.X.10
 
 # General parameters (can also given on command line)
 params:
diff --git a/notebooks/config_mask.yaml b/config/calibration/mask_v1.X.11.yaml
similarity index 72%
rename from notebooks/config_mask.yaml
rename to config/calibration/mask_v1.X.11.yaml
index 4af95017..13e9187f 100644
--- a/notebooks/config_mask.yaml
+++ b/config/calibration/mask_v1.X.11.yaml
@@ -1,14 +1,21 @@
+# Config file for masking and calibration.
+# Standard cuts without halo masks, including deblended objects, type v1.X.11
+
+# General parameters (can also given on command line)
 params:
-  input_path: unions_shapepipe_comprehensive_struc_2024_v1.4.2.hdf5
-  cmatrices: True
+  input_path: unions_shapepipe_comprehensive_struc_2024_v1.X.c.hdf5
+  cmatrices: False
+  sky_regions: False
   verbose: True
 
+# Masks
+## Using columns in 'dat' group (ShapePipe flags)
 dat:
   # SExtractor flags
   - col_name: FLAGS
     label: SE FLAGS
-    kind: equal
-    value: 0
+    kind: smaller_equal
+    value: 3
 
   # Duplicate objects
   - col_name: overlap
@@ -50,18 +57,8 @@ dat:
     kind: not_equal
     value: -10
 
+## Using columns in 'dat_ext' group (post-processing flags)
 dat_ext:
-  # Faint star halos
-  - col_name: 1_Faint_star_halos
-    label: "Faint star halos"
-    kind: equal
-    value: False
-
-  # Bright star halos
-  - col_name: 2_Bright_star_halos
-    label: "Bright star halos"
-    kind: equal
-    value: False
 
   # Stars
   - col_name: 4_Stars
@@ -87,7 +84,7 @@ dat_ext:
     kind: equal
     value: False
 
-  # Rought pointing coverage
+  # Rough pointing coverage
   - col_name: npoint3
     label: r"$n_{\rm pointing}$"
     kind: greater_equal
@@ -103,8 +100,11 @@ metacal:
   gal_snr_max: 500
 
   # Relative-size (hlr / hlr_psf) range
-  gal_rel_size_min: 0.5
+  gal_rel_size_min: 0.707
   gal_rel_size_max: 3
 
   # Correct relative size for ellipticity?
-  gal_size_corr_ell: False
\ No newline at end of file
+  gal_size_corr_ell: False
+
+  # Weight for global response matrix, None for unweighted mean
+  global_R_weight: w
diff --git a/config/calibration/mask_v1.X.2.yaml b/config/calibration/mask_v1.X.2.yaml
index 46672c04..7d93a57a 100644
--- a/config/calibration/mask_v1.X.2.yaml
+++ b/config/calibration/mask_v1.X.2.yaml
@@ -116,3 +116,14 @@ metacal:
 
   # Correct relative size for ellipticity?
   gal_size_corr_ell: False
+
+# Binned footprint mask
+binned_mask:
+  # Resolution
+  nside: 8192
+
+  # Mask value for "good region (observed)
+  good: False
+
+  # Output file path
+  output_path: "footprint_binned.fits"
diff --git a/config/calibration/mask_v1.X.3.yaml b/config/calibration/mask_v1.X.3.yaml
index 96aeecd5..242031a8 100644
--- a/config/calibration/mask_v1.X.3.yaml
+++ b/config/calibration/mask_v1.X.3.yaml
@@ -99,3 +99,14 @@ metacal:
 
   # Correct relative size for ellipticity?
   gal_size_corr_ell: False
+
+# Binned footprint mask
+binned_mask:
+  # Resolution
+  nside: 8192
+
+  # Mask value for "good region (observed)
+  good: False
+
+  # Output file path
+  output_path: "footprint_binned.fits"
diff --git a/config/calibration/mask_v1.X.4.yaml b/config/calibration/mask_v1.X.4.yaml
index 6db36f6b..59080851 100644
--- a/config/calibration/mask_v1.X.4.yaml
+++ b/config/calibration/mask_v1.X.4.yaml
@@ -110,3 +110,14 @@ metacal:
 
   # Correct relative size for ellipticity?
   gal_size_corr_ell: False
+
+# Binned footprint mask
+binned_mask:
+  # Resolution
+  nside: 8192
+
+  # Mask value for "good region (observed)
+  good: False
+
+  # Output file path
+  output_path: "footprint_binned.fits"
diff --git a/config/calibration/mask_v1.X.5.yaml b/config/calibration/mask_v1.X.5.yaml
index 6fa04aff..7fb14835 100644
--- a/config/calibration/mask_v1.X.5.yaml
+++ b/config/calibration/mask_v1.X.5.yaml
@@ -105,3 +105,14 @@ metacal:
 
   # Correct relative size for ellipticity?
   gal_size_corr_ell: False
+
+# Binned footprint mask
+binned_mask:
+  # Resolution
+  nside: 8192
+
+  # Mask value for "good region (observed)
+  good: False
+
+  # Output file path
+  output_path: "footprint_binned.fits"
diff --git a/config/calibration/mask_v1.X.6.yaml b/config/calibration/mask_v1.X.6.yaml
index 9dee1944..0ea23f47 100644
--- a/config/calibration/mask_v1.X.6.yaml
+++ b/config/calibration/mask_v1.X.6.yaml
@@ -108,3 +108,14 @@ metacal:
 
   # Weight for global response matrix, None for unweighted mean
   global_R_weight: w
+
+# Binned footprint mask
+binned_mask:
+  # Resolution
+  nside: 8192
+
+  # Mask value for "good region (observed)
+  good: False
+
+  # Output file path
+  output_path: "footprint_binned.fits"
diff --git a/config/calibration/mask_v1.X.7.yaml b/config/calibration/mask_v1.X.7.yaml
index 49325e36..830d7a28 100644
--- a/config/calibration/mask_v1.X.7.yaml
+++ b/config/calibration/mask_v1.X.7.yaml
@@ -113,3 +113,14 @@ metacal:
 
   # Weight for global response matrix, None for unweighted mean
   global_R_weight: w
+
+# Binned footprint mask
+binned_mask:
+  # Resolution
+  nside: 8192
+
+  # Mask value for "good region (observed)
+  good: False
+
+  # Output file path
+  output_path: "footprint_binned.fits"
diff --git a/config/calibration/mask_v1.X.8.yaml b/config/calibration/mask_v1.X.8.yaml
index c346b339..bd74e54b 100644
--- a/config/calibration/mask_v1.X.8.yaml
+++ b/config/calibration/mask_v1.X.8.yaml
@@ -119,3 +119,14 @@ metacal:
 
   # Weight for global response matrix, None for unweighted mean
   global_R_weight: w
+
+# Binned footprint mask
+binned_mask:
+  # Resolution
+  nside: 8192
+
+  # Mask value for "good region (observed)
+  good: False
+
+  # Output file path
+  output_path: "footprint_binned.fits"
diff --git a/notebooks/calibrate_comprehensive_cat.py b/notebooks/calibrate_comprehensive_cat.py
index 168d608c..5d5a8be0 100644
--- a/notebooks/calibrate_comprehensive_cat.py
+++ b/notebooks/calibrate_comprehensive_cat.py
@@ -8,9 +8,10 @@
 # enable autoreload for interactive sessions                                     
 ipython = get_ipython()                                                          
 if ipython is not None:                                                          
-    ipython.run_line_magic("load_ext", "autoreload")                             
+    ipython.run_line_magic("reload_ext", "autoreload")                             
     ipython.run_line_magic("autoreload", "2")
-    ipython.run_line_magic("load_ext", "log_cell_time")
+    ipython.run_line_magic("reload_ext", "log_cell_time")
+
 
 # %%
 import sys
@@ -36,6 +37,11 @@
 # Read configuration file and set parameters
 config = obj.read_config_set_params("config_mask.yaml")
 
+
+
+# %%
+obj._params
+
 # %%
 # Get data. Set load_into_memory to False for very large files
 dat, dat_ext = obj.read_cat(load_into_memory=False)
@@ -49,7 +55,6 @@
     dat_ext = dat_ext[:n_test]
 
 
-
 # %%
 # ## Masking
 
@@ -125,6 +130,10 @@
     mask_combined,
     mask_metacal,
     num_bins=20,
+    snr_min=cm["gal_snr_min"],
+    snr_max=cm["gal_snr_max"],
+    size_ratio_min=cm["gal_rel_size_min"],
+    size_ratio_max=cm["gal_rel_size_max"],
 )
 
 # %%
@@ -195,7 +204,14 @@
         mask_combined._mask,
         mask_metacal
     )
-    #add_cols_data[key] = dat[key][mask_combined._mask][mask_metacal]
+
+# Keep original NOSHEAR column, override with 1P PSF values (FHP/MK hack)
+print(
+    "FHP/MK hack: explicit copying of the metacal no-shear (updated from 1p)"
+    + f" PSF size"
+)
+add_cols_data["NGMIX_Tpsf_NOSHEAR_orig"] = add_cols_data["NGMIX_Tpsf_NOSHEAR"]
+add_cols_data["NGMIX_Tpsf_NOSHEAR"] = gal_metacal.ns["Tpsf"][mask_metacal]
 
 # %%
 # Additional post-processing columns to write to output cat
@@ -229,10 +245,6 @@
 for my_mask in masks:
     my_mask.add_summary_to_FITS_header(header)
 
-
-# %%
-header
-
 # %%
 output_shape_cat_path = obj._params["input_path"].replace(
     "comprehensive", "cut"
diff --git a/notebooks/cosmo_val/cat_config.yaml b/notebooks/cosmo_val/cat_config.yaml
index 83c7a357..8a8e22eb 100644
--- a/notebooks/cosmo_val/cat_config.yaml
+++ b/notebooks/cosmo_val/cat_config.yaml
@@ -161,7 +161,7 @@ SP_v1.3:
 SP_v1.3.6:
   subdir: /n17data/UNIONS/WL/v1.3.x
   pipeline: SP
-  colour: violet
+  colour: coral
   getdist_colour: 0.0, 0.5, 1.0
   ls: dashed
   marker: h
@@ -646,7 +646,7 @@ SP_v1.4.8:
 SP_v1.4.11.2:
   subdir: /n17data/UNIONS/WL/v1.4.x
   pipeline: SP
-  colour: blue
+  colour: orange
   getdist_colour: 0.0, 0.5, 1.0
   ls: dashed
   marker: s
@@ -688,18 +688,18 @@ SP_v1.4.11.2:
     e1_col: e1
     e2_col: e2
     path: unions_shapepipe_star_2024_v1.4.a.fits
-SP_v1.4.11.2_w_iv:
+SP_v1.4.11.3:
   subdir: /n17data/UNIONS/WL/v1.4.x
   pipeline: SP
-  colour: teal
-  getdist_colour: 0.0, 0.7, 0.7
-  ls: dotted
-  marker: s
+  colour: red
+  getdist_colour: 0.0, 0.5, 1.0
+  ls: dashdot
+  marker: v
   cov_th:
     A: 2405.3892055695346
-    n_e: 7.529428768078532
+    n_e: 6.128201234871523
     n_psf: 0.752316232272063
-    sigma_e: 0.380499698062307
+    sigma_e: 0.379587601488189
   mask: /home/guerrini/sp_validation/cosmo_inference/data/mask/mask_map_v1.4.6_nside_8192.fits
   psf:
     PSF_flag: FLAG_PSF_HSM
@@ -718,9 +718,9 @@ SP_v1.4.11.2_w_iv:
   shear:
     R: 1.0
     covmat_file: ./covs/shapepipe_A/cov_shapepipe_A.txt
-    path: v1.4.11.2/unions_shapepipe_cut_struc_2024_v1.4.11.2.fits
+    path: v1.4.11.3/unions_shapepipe_cut_struc_2024_v1.4.11.3.fits
     redshift_path: /n17data/mkilbing/astro/data/CFIS/v1.0/nz/dndz_SP_A.txt
-    w_col: w_iv
+    w_col: w_des
     e1_col: e1
     e1_col_corrected: e1_leak_corrected
     e1_PSF_col: e1_PSF
diff --git a/notebooks/create_shear_mb_empty.py b/notebooks/create_shear_mb_empty.py
index 9c3d1760..6d29bfc2 100644
--- a/notebooks/create_shear_mb_empty.py
+++ b/notebooks/create_shear_mb_empty.py
@@ -39,7 +39,7 @@
 # Set parameters
 base = "unions_shapepipe_comprehensive_struc"
 year = 2024
-ver = "v1.5.c"
+ver = "v1.6.c"
 
 obj._params = {}
 
diff --git a/notebooks/demo_apply_hsp_masks.py b/notebooks/demo_apply_hsp_masks.py
index 1760cd7f..a264bb1d 100644
--- a/notebooks/demo_apply_hsp_masks.py
+++ b/notebooks/demo_apply_hsp_masks.py
@@ -57,7 +57,8 @@
 # +
 # Set parameters
 base = "unions_shapepipe_comprehensive"
-year = 2024
+ver = "v1.3.c"
+
 if ver == "v1.3.c":
     year = 2022
 else:
diff --git a/notebooks/extract_info.py b/notebooks/extract_info.py
index 0bddceab..a4e33451 100644
--- a/notebooks/extract_info.py
+++ b/notebooks/extract_info.py
@@ -175,7 +175,6 @@
     g_star_psf[1],
 )
 
-
 #### Refine: Match to SPREAD_CLASS samples
 if "SPREAD_CLASS" in dd.dtype.names:
     spv_cat.match_spread_class(dd, ind_star, m_star, stats_file, len(ra_star), verbose=verbose)
diff --git a/pyproject.toml b/pyproject.toml
index 15912c95..5329a120 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -20,7 +20,6 @@ dependencies = [
     "camb",
     "clmm",
     "colorama",
-    "cosmo-numba @ git+https://github.com/aguinot/cosmo-numba",
     "cs_util>=0.1.5",
     "emcee",
     "getdist @ git+https://github.com/benabed/getdist.git@upper_triangle_whisker",
diff --git a/src/sp_validation/basic.py b/src/sp_validation/basic.py
index 9767ad79..8eed0eca 100644
--- a/src/sp_validation/basic.py
+++ b/src/sp_validation/basic.py
@@ -145,6 +145,15 @@ def _read_data(self, data, mask):
                 ns,
             )
 
+        print("FHP/MK hack using p1 PSF for ns in cuts")
+        indices = np.where(mask)[0]
+        col_noshear = f"{self._prefix}_Tpsf_NOSHEAR"
+        col_1p = f"{self._prefix}_Tpsf_1P"
+        new_psf = data[col_1p][indices]
+
+        # Overwriting incorrect no-shear PSF size to the one from 1p
+        ns["Tpsf"] = new_psf
+
         self.m1 = m1
         self.p1 = p1
         self.m2 = m2
@@ -157,7 +166,7 @@ def _read_data_ngmix(self, masked_data, m1, p1, m2, p2, ns):
         Read data from ngmix catalogue.
         
         """
-        
+
         for name_shear, dict_tmp in zip(
             ['1M', '1P', '2M', '2P', 'NOSHEAR'],
             [m1, p1, m2, p2, ns]
@@ -370,14 +379,7 @@ def _masking_gal(self):
             else:
                 snr_flux = data['flux'] / data['flux_err']
 
-            if name == 'ns':
-                # This is a FHP hack, the ns PSF measured in shapepipe is not correct,
-                # fortunately it is the same dilated PSF as the other branches,
-                # thus we can simply use p1
-                print("FHP using p1 PSF for ns in cuts")
-                Tpsf = self.p1['Tpsf']
-            else:
-                Tpsf = data['Tpsf']
+            Tpsf = data['Tpsf']
 
             mask_tmp = (
                 (data['flag'] == 0)
diff --git a/src/sp_validation/calibration.py b/src/sp_validation/calibration.py
index a4368f99..0272822a 100644
--- a/src/sp_validation/calibration.py
+++ b/src/sp_validation/calibration.py
@@ -244,7 +244,14 @@ def build_df(cat_gal):
     return pd.DataFrame(arr, columns=cat_gal.keys())
     
 
-def get_w_des(cat_gal, num_bins):
+def get_w_des(
+    cat_gal,
+    num_bins,
+    snr_min=None,
+    snr_max=None,
+    size_ratio_min=None,
+    size_ratio_max=None,
+):
     """
     Get DES weights. (Gatti et al. 2021)
     Return an array of DES weights obtained by binning in SNR and size and computing the ratio between
@@ -253,9 +260,18 @@ def get_w_des(cat_gal, num_bins):
     Parameters
     ----------
     cat_gal: dict
-        A catalog of galaxies containing the response matrix and the uncalibrated ellipticities
+        A catalog of galaxies containing the response matrix and the
+        uncalibrated ellipticities
     num_bins : int
         Number of bins to use for the binning of the SNR and size.
+    snr_min : float, optional
+        Minimum SNR, default (`None`): determined by the data
+    snr_max : float, optional
+        Maximum SNR, default (`None`): determined by the data
+    size_ratio_min : float, optional
+        Minimum size ratio, default (`None`): determined by the data
+    size_ratio_max : float, optional
+        Maximum size ratio, default (`None`): determined by the data
 
     Returns
     -------
@@ -266,11 +282,24 @@ def get_w_des(cat_gal, num_bins):
     df_gal = build_df(cat_gal)
 
     #Create logarithmic bins in size and SNR
-    cut_to_bins(df_gal, "snr", num_bins, type="log")
-    cut_to_bins(df_gal, "size_ratio", num_bins, type="log")
-
-    #Compute shape noise and the shear response in each bin
+    cut_to_bins(
+        df_gal,
+        "snr",
+        num_bins,
+        type="log",
+        x_min=snr_min,
+        x_max=snr_max,
+    )
+    cut_to_bins(
+        df_gal,
+        "size_ratio",
+        num_bins,
+        type="log",
+        x_min=size_ratio_min,
+        x_max=size_ratio_max,
+    )
 
+    # Compute shape noise and the shear response in each bin
     for i in range(num_bins):
         for j in range(num_bins):
             bin_mask = (
@@ -496,7 +525,7 @@ def get_quantities_binned(cat_gal, num_bins_x, num_bins_y=None, which=["response
     
     # Create logarithmic bins in size and SNR
     bin_edges = {}
-    bin_edges["snr"] = cut_to_bins(df_gal, "snr", num_bins_x, type="log", x_min=3, x_max=700)
+    bin_edges["snr"] = cut_to_bins(df_gal, "snr", num_bins_x, type="log", x_min=2, x_max=700)
     bin_edges["size_ratio"] = cut_to_bins(df_gal, "size_ratio", num_bins_y, type="log", x_min=0.3, x_max=10)
     
     # Initialize output dict
diff --git a/src/sp_validation/cosmo_val.py b/src/sp_validation/cosmo_val.py
index f314c2fe..b19b67de 100644
--- a/src/sp_validation/cosmo_val.py
+++ b/src/sp_validation/cosmo_val.py
@@ -1798,8 +1798,8 @@ def plot_ratio_xi_sys_xi(self, threshold=0.1, offset=0.02):
 
         fig, _ = plt.subplots(ncols=1, nrows=1, figsize=(10, 7))
 
-
         for idx, ver in enumerate(self.versions):
+            self.calculate_2pcf(ver)
             xi_psf_sys = self.xi_psf_sys[ver]
             gg = self.cat_ggs[ver]
 
@@ -1967,7 +1967,7 @@ def plot_aperture_mass_dispersion(self):
                 labels=labels,
                 xlog=True,
                 xlim=[self.theta_min_plot, self.theta_max_plot],
-                ylim=[-1e-6, 2e-5],
+                ylim=[-2e-6, 5e-6],
                 colors=colors,
                 linestyles=linestyles,
                 shift_x=True,
@@ -2000,7 +2000,7 @@ def plot_aperture_mass_dispersion(self):
                 xlog=True,
                 ylog=True,
                 xlim=[self.theta_min_plot, self.theta_max_plot],
-                ylim=[1e-9, 3e-5],
+                ylim=[1e-8, 1e-5],
                 colors=colors,
                 linestyles=linestyles,
                 shift_x=True,
diff --git a/src/sp_validation/run_joint_cat.py b/src/sp_validation/run_joint_cat.py
index 0b17d274..51a4d84e 100644
--- a/src/sp_validation/run_joint_cat.py
+++ b/src/sp_validation/run_joint_cat.py
@@ -1143,7 +1143,7 @@ def read_cat(self, load_into_memory=False):
         except:
             print(f"Error while reading file {fpath}")
             raise
-   
+
         if verbose:
             print(
                 f"Found {len(dat)} (~{util.millify(len(dat))}) objects"
@@ -1565,6 +1565,10 @@ def compute_weights_gatti(
     mask_combined,
     mask_metacal,
     num_bins=20,
+    snr_min=10,
+    snr_max=500,
+    size_ratio_min=0.707,
+    size_ratio_max=3,
 ):
     """Compute Weights Gatti.
     
@@ -1581,7 +1585,14 @@ def compute_weights_gatti(
         purpose="weights"
     )
 
-    cat_gal["w_des"] = calibration.get_w_des(cat_gal, num_bins)
+    cat_gal["w_des"] = calibration.get_w_des(
+        cat_gal,
+        num_bins,
+        snr_min=snr_min,
+        snr_max=snr_max,
+        size_ratio_min=size_ratio_min,
+        size_ratio_max=size_ratio_max,
+    )
 
 
 def compute_PSF_leakage(