diff --git a/etx4velo/analyses/check_tracks_with_clones.ipynb b/etx4velo/analyses/check_tracks_with_clones.ipynb
index e3094df1620159fb2f89bcbb109f5c87ce44ee19..1a5a3a21ad50bf610886e65a69f83fa2a25fe098 100644
--- a/etx4velo/analyses/check_tracks_with_clones.ipynb
+++ b/etx4velo/analyses/check_tracks_with_clones.ipynb
@@ -23,7 +23,7 @@
     "\n",
     "from utils.plotutils.plotconfig import configure_matplotlib\n",
     "from utils.commonutils.cfeatures import get_unnormalised_features\n",
-    "from Scripts.Step_6_Evaluate_Reconstruction_MonteTracko import (\n",
+    "from scripts.evaluate import (\n",
     "    get_tracks_from_batch,\n",
     "    perform_matching,\n",
     ")\n",
@@ -1268,7 +1268,7 @@
     "    TripletInteractionGNN,\n",
     "    correct_shared_hits_triplets,\n",
     ")\n",
-    "from Scripts.Step_5_Build_Track_Candidates_Triplets import (\n",
+    "from scripts.track_building import (\n",
     "    get_filtered_triplet_indices,\n",
     "    count_occurences,\n",
     "    swap_values_in_tensor,\n",
diff --git a/etx4velo/evaluation/embedding/plot_embedding_best_tracking_performance.py b/etx4velo/evaluation/embedding/plot_embedding_best_tracking_performance.py
index bd3fd7409bbb9bdbdc1b3355c56e20e60483f42b..d187cc9ad74cba1eeed9077838a9203b9a752d61 100644
--- a/etx4velo/evaluation/embedding/plot_embedding_best_tracking_performance.py
+++ b/etx4velo/evaluation/embedding/plot_embedding_best_tracking_performance.py
@@ -57,10 +57,19 @@ if __name__ == "__main__":
         seed=0,
         builder=builder,
         categories=[
-            mtb.category.category_velo_no_electrons,
+            mtb.category.category_only_velo_no_electrons,
+            mtb.category.category_only_velo_only_electrons,
+            mtb.category.category_long_no_electrons,
             mtb.category.category_long_only_electrons,
             mtb.category.category_long_strange,
         ],
+        category_name_to_color={
+            mtb.category.category_only_velo_no_electrons.name: "#fe9929",
+            mtb.category.category_only_velo_only_electrons.name: "#cc4c02",
+            mtb.category.category_long_no_electrons.name: "#74a9cf",
+            mtb.category.category_long_only_electrons.name: "#0570b0",
+            mtb.category.category_long_strange.name: "purple",
+        },
         output_path=output_wpath,
         same_fig=False,
         lhcb=True,
diff --git a/etx4velo/evaluation/gnn/plot_gnn_best_tracking_performance.py b/etx4velo/evaluation/gnn/plot_gnn_best_tracking_performance.py
index 8fe217e9f8d7793b7c2e6b88b681ef5e17a9fd4c..810b5eb6a54c9550c51ff69126e3c2a1d533acab 100644
--- a/etx4velo/evaluation/gnn/plot_gnn_best_tracking_performance.py
+++ b/etx4velo/evaluation/gnn/plot_gnn_best_tracking_performance.py
@@ -75,15 +75,23 @@ if __name__ == "__main__":
             0.4,
             0.5,
             0.7,
-            0.9,
         ],
         n_events=n_events,
         seed=0,
         categories=[
-            mtb.category.category_velo_no_electrons,
+            mtb.category.category_only_velo_no_electrons,
+            mtb.category.category_only_velo_only_electrons,
+            mtb.category.category_long_no_electrons,
             mtb.category.category_long_only_electrons,
             mtb.category.category_long_strange,
         ],
+        category_name_to_color={
+            mtb.category.category_only_velo_no_electrons.name: "#fe9929",
+            mtb.category.category_only_velo_only_electrons.name: "#cc4c02",
+            mtb.category.category_long_no_electrons.name: "#74a9cf",
+            mtb.category.category_long_only_electrons.name: "#0570b0",
+            mtb.category.category_long_strange.name: "purple",
+        },
         track_metric_names=["ghost_rate"],
         same_fig=False,
         lhcb=True,
diff --git a/etx4velo/pipeline/Embedding/embedding_plots.py b/etx4velo/pipeline/Embedding/embedding_plots.py
index 26201d22fcd83b6f329bad05d2084334b41ed52a..fc59601498fcee49d3911d1d2dab870031f7384b 100644
--- a/etx4velo/pipeline/Embedding/embedding_plots.py
+++ b/etx4velo/pipeline/Embedding/embedding_plots.py
@@ -25,6 +25,11 @@ metric_name_to_lhcb_text_params: typing.Dict[str, typing.Dict[str, typing.Any]]
     "edge_purity": {"ha": "right", "va": "top"},
     "graph_size": {"ha": "left", "va": "top"},
 }
+metric_name_to_label: typing.Dict[str, str] = {
+    "edge_efficiency": "Average graph edge efficiency",
+    "edge_purity": "Average graph edge purity",
+    "graph_size": "\\# graph edges",
+}
 
 
 def plot_embedding_performance_given_squared_distance_max_k_max(
@@ -139,7 +144,7 @@ def plot_embedding_performance_given_squared_distance_max_k_max(
             ]
         ):
             ax.legend()
-        ax.set_ylabel(metric_name.replace("_", " ").title())
+        ax.set_ylabel(metric_name_to_label[metric_name])
 
         if lhcb:
             add_text(ax, **metric_name_to_lhcb_text_params[metric_name])
diff --git a/etx4velo/pipeline/Evaluation/plotting.py b/etx4velo/pipeline/Evaluation/plotting.py
index d317f2e0572eb356d9d8df9c41e4dd3aec4d7c73..6a7fc244941d942f0de7f7bb77ba99ce27521d9e 100644
--- a/etx4velo/pipeline/Evaluation/plotting.py
+++ b/etx4velo/pipeline/Evaluation/plotting.py
@@ -171,17 +171,22 @@ def plot_histograms_trackevaluator(
                 column_label=column_labels.get(column, column.replace("_", r"\_")),
                 ax=axes[idx_metric][idx_col],
             )
+            
+            alpha = 0.65 if len(trackEvaluators) > 1 else 1.0
 
             (
                 axes_histogram[idx_metric][idx_col],
                 _,
                 _,
                 edges,
+                _,
             ) = trackEvaluators[0].plot_histogram(
                 range=column_ranges.get(column),
                 bins=bins_metric,
                 color=colors[0],
                 label=labels[0],
+                err="auto",
+                alpha=alpha,
                 **histogram_common_kwargs,
                 **kwargs,
             )
@@ -192,7 +197,9 @@ def plot_histograms_trackevaluator(
                     bins=edges,
                     color=color,
                     label=label,
+                    err="auto",
                     show_histogram=False,
+                    alpha=alpha,
                     **histogram_common_kwargs,
                     **kwargs,
                 )
diff --git a/etx4velo/pipeline/utils/modelutils/exploration.py b/etx4velo/pipeline/utils/modelutils/exploration.py
index 6106cd3256d4391422418a5549e49664f435c1e6..711482000ed9037cb5b567f57dc21f01587211ed 100644
--- a/etx4velo/pipeline/utils/modelutils/exploration.py
+++ b/etx4velo/pipeline/utils/modelutils/exploration.py
@@ -24,6 +24,21 @@ from .basemodel import ModelBase
 from ..loaderutils.dataiterator import LazyDatasetBase
 
 
+def _get_metric_errors(values, dict_performances, metric_name, category_name):
+    metric_errors = []
+    for value in values:
+        output = dict_performances[value][category_name, metric_name]
+        if "err_pos" in output and "err_neg" in output:
+            metric_errors.append([output["err_neg"], output["err_pos"]])
+        elif "err" in output:
+            metric_errors.append(output["err"])
+        else:
+            raise Exception(
+                "Neither `err_pos` and `err_neg`, not `err` " "is in the dictionary."
+            )
+    return np.array(metric_errors).T
+
+
 class ParamExplorer(abc.ABC):
     """A class that allow to explore the track matching performance for various choices
     of a given parameter of a trained model (e.g., best efficiency as a function
@@ -94,7 +109,9 @@ class ParamExplorer(abc.ABC):
         seed: int | None = None,
         track_metric_names: typing.List[str] | None = None,
         **kwargs,
-    ) -> typing.Dict[float, typing.Dict[typing.Tuple[str | None, str], float]]:
+    ) -> typing.Dict[
+        float, typing.Dict[typing.Tuple[str | None, str], typing.Dict[str, float]]
+    ]:
         """Compute the performance metrics for different values a hyperparameter.
 
         Args:
@@ -152,7 +169,7 @@ class ParamExplorer(abc.ABC):
         metric_names: typing.List[str],
         categories: typing.List[mt.requirement.Category],
         track_metric_names: typing.List[str] | None = None,
-    ) -> typing.Dict[typing.Tuple[str | None, str], float]:
+    ) -> typing.Dict[typing.Tuple[str | None, str], typing.Dict[str, float]]:
         """Get performance dictionary for given tracks.
 
         Args:
@@ -176,10 +193,11 @@ class ParamExplorer(abc.ABC):
         if track_metric_names is None:
             track_metric_names = []
 
-        dict_performances: typing.Dict[typing.Tuple[str | None, str], float] = {
+        dict_performances: typing.Dict[typing.Tuple[str | None, str], typing.Dict[str, float]] = {  # type: ignore
             (category.name, metric_name): trackEvaluator.compute_metric(
                 metric_name=metric_name,
                 category=category,
+                err="auto",
             )
             for category in categories
             for metric_name in metric_names
@@ -188,6 +206,7 @@ class ParamExplorer(abc.ABC):
             dict_performances[None, track_metric_name] = trackEvaluator.compute_metric(
                 metric_name=track_metric_name,
                 category=None,
+                err="auto",
             )
         return dict_performances
 
@@ -226,11 +245,14 @@ class ParamExplorer(abc.ABC):
         output_path: str | None = None,
         same_fig: bool = True,
         lhcb: bool = False,
+        category_name_to_color: dict | None = None,
         **kwargs,
     ) -> typing.Tuple[
         Figure | npt.NDArray,
         typing.List[Axes],
-        typing.Dict[float, typing.Dict[typing.Tuple[str | None, str], float]],
+        typing.Dict[
+            float, typing.Dict[typing.Tuple[str | None, str], typing.Dict[str, float]]
+        ],
     ]:
         """Plot metrics in differences categories for different hyperparameter
         values.
@@ -262,6 +284,9 @@ class ParamExplorer(abc.ABC):
             3-tuple of the Matplotlib Figures and Axes, and the dictionary of
             metric values for every tuple ``(value, category.name, metric_name)``
         """
+        if category_name_to_color is None:
+            category_name_to_color = {}
+
         if metric_names is None:
             metric_names = ["efficiency", "clone_rate", "hit_efficiency_per_candidate"]
         if categories is None:
@@ -286,9 +311,46 @@ class ParamExplorer(abc.ABC):
         if track_metric_names is None:
             track_metric_names = []
 
-        figs, axes_ = plotools.get_figs_axes_on_grid(
-            1, len(metric_names) + len(track_metric_names), same_fig=same_fig
-        )
+        if same_fig:
+            figs, axes_ = plotools.get_figs_axes_on_grid(
+                1,
+                len(metric_names) + len(track_metric_names),
+                same_fig=True,
+                figsize=(8, 6),
+            )
+        else:
+            if metric_names:
+                figs_with_cat, axes_with_cat_ = plotools.get_figs_axes_on_grid(
+                    1,
+                    len(metric_names),
+                    same_fig=False,
+                    figsize=(12, 6),
+                )
+            else:
+                figs_with_cat = None
+                axes_with_cat_ = None
+
+            if track_metric_names:
+                figs_track, axes_track_ = plotools.get_figs_axes_on_grid(
+                    1,
+                    len(track_metric_names),
+                    same_fig=False,
+                    figsize=(8, 6),
+                )
+            else:
+                figs_track = None
+                axes_track_ = None
+
+            figs = np.concatenate(
+                [figs_ for figs_ in (figs_with_cat, figs_track) if figs_ is not None],
+            )
+            axes_ = np.concatenate(
+                [
+                    axes__
+                    for axes__ in (axes_with_cat_, axes_track_)
+                    if axes__ is not None
+                ],
+            )
 
         axes = np.atleast_1d(axes_).tolist()
 
@@ -297,12 +359,24 @@ class ParamExplorer(abc.ABC):
             axes[metric_idx].grid(color="grey", alpha=0.5)
             for category in categories:
                 metric_values = [
-                    dict_performances[value][category.name, metric_name]
+                    dict_performances[value][category.name, metric_name]["mean"]
                     for value in values
                 ]
 
-                axes[metric_idx].plot(
-                    values, metric_values, label=category.label, marker="."
+                metric_errors = _get_metric_errors(
+                    values=values,
+                    dict_performances=dict_performances,
+                    metric_name=metric_name,
+                    category_name=category.name,
+                )
+
+                axes[metric_idx].errorbar(
+                    values,
+                    metric_values,
+                    label=category.label,
+                    marker=".",
+                    yerr=metric_errors,
+                    color=category_name_to_color.get(category.name),
                 )
 
         for rel_track_metric_idx, track_metric_name in enumerate(track_metric_names):
@@ -311,21 +385,35 @@ class ParamExplorer(abc.ABC):
                 mt.metricsLibrary.label(track_metric_name)
             )
             metric_values = [
-                dict_performances[value][None, track_metric_name] for value in values
+                dict_performances[value][None, track_metric_name]["mean"]
+                for value in values
             ]
-            axes[track_metric_idx].plot(values, metric_values, marker=".", color="k")
+            metric_errors = _get_metric_errors(
+                values=values,
+                dict_performances=dict_performances,
+                metric_name=track_metric_name,
+                category_name=None,
+            )
+            axes[track_metric_idx].errorbar(
+                values,
+                metric_values,
+                marker=".",
+                color="k",
+                yerr=metric_errors,
+            )
 
         for ax, metric_name in zip(axes, metric_names + track_metric_names):
             ax.set_xlabel(self.varlabel)
             ax.grid(color="grey", alpha=0.5)
             if lhcb:
-                self.add_lhcb_text(ax=ax, metric_name=metric_name)
+                plotools.pad_on_top(ax=ax)
+                plotools.add_text(ax=ax, ha="left", va="top")
 
         if same_fig:
             axes[0].legend()
         else:
             for metric_idx, _ in enumerate(metric_names):
-                axes[metric_idx].legend()
+                axes[metric_idx].legend(loc="center left", bbox_to_anchor=(1, 0.5))
 
         if same_fig:
             if output_path is None:
diff --git a/etx4velo/pipeline/utils/plotutils/performance_mpl.py b/etx4velo/pipeline/utils/plotutils/performance_mpl.py
index bfff7280215f9bc0729a3eef0cf7a71d15ec10cc..acc21e512b377bf95548730c6b486c2a1b2bda9e 100644
--- a/etx4velo/pipeline/utils/plotutils/performance_mpl.py
+++ b/etx4velo/pipeline/utils/plotutils/performance_mpl.py
@@ -21,7 +21,10 @@ from .plotools import save_fig, add_text
 from .plotconfig import partition_to_color, partition_to_label
 
 
-metric_labels = {"eff": "Edge Efficiency", "pur": "Edge Purity"}
+metric_labels = {
+    "eff": "Average edge efficiency per event",
+    "pur": "Average edge purity per event",
+}
 metric_colors = {"eff": "purple", "pur": "blue"}
 
 
diff --git a/etx4velo/pipeline/utils/plotutils/plotconfig.py b/etx4velo/pipeline/utils/plotutils/plotconfig.py
index eb7dd76fe762052245b9d7b7d7494b424d7e8483..ddb18d2541bf2c90ca668313c048540cdf4bbd45 100644
--- a/etx4velo/pipeline/utils/plotutils/plotconfig.py
+++ b/etx4velo/pipeline/utils/plotutils/plotconfig.py
@@ -42,7 +42,7 @@ column_ranges = {
     "pt": (0, 2000),
     "p": (0, 50000),
     "eta": (2.0, 5.0),
-    "vz": (-200, 700),
+    "vz": (-200, 650),
     "distance_to_line": (0.0, 0.15),
     "distance_to_z_axis": (0.0, 0.10),
     # "xz_angle": (0.0, 0.5),
diff --git a/etx4velo/pipeline/utils/plotutils/plotools.py b/etx4velo/pipeline/utils/plotutils/plotools.py
index 832371dc107aa6829f4c6a57d8267504b5de7311..a162ba65e3900c79abe306be9e0729655b60ec94 100644
--- a/etx4velo/pipeline/utils/plotutils/plotools.py
+++ b/etx4velo/pipeline/utils/plotutils/plotools.py
@@ -33,24 +33,29 @@ def get_figs_axes_on_grid(
 
 
 def get_figs_axes_on_grid(
-    nrows: int, ncols: int, same_fig: bool = True, **kwargs
+    nrows: int,
+    ncols: int,
+    same_fig: bool = True,
+    figsize: typing.Tuple[int, int] | typing.List[typing.Tuple[int, int]] = (8, 6),
+    **kwargs,
 ) -> typing.Tuple[Figure | npt.NDArray, npt.NDArray]:
     if same_fig:
         fig, axes = plt.subplots(
             nrows,
             ncols,
-            figsize=(8 * ncols, 6 * nrows),
+            figsize=(figsize[0] * ncols, figsize[1] * nrows),
             **kwargs,
         )
         return fig, axes
     else:
+
         figs = []
         axes = []
         for _ in range(nrows):
             line_figs = []
             line_axes = []
             for _ in range(ncols):
-                fig, ax = plt.subplots(figsize=(8, 6), **kwargs)
+                fig, ax = plt.subplots(figsize=figsize, **kwargs)
                 line_figs.append(fig)
                 line_axes.append(ax)
             figs.append(line_figs)
@@ -76,8 +81,8 @@ def add_text(
     va: str | None = None,
     x: float | None = None,
     y: float | None = None,
-    text: str = "LHCb Simulation",
-    fontsize: float | None = 23,
+    text: str = "LHCb Run 3 Simulation",
+    fontsize: float | None = 20,
     **kwargs,
 ) -> Text:
     """Add text inside a matplotlib figure.
diff --git a/etx4velo/pipeline/utils/plotutils/tracks.py b/etx4velo/pipeline/utils/plotutils/tracks.py
index f8508da8875876ecc4438e73aa5846f91fa12ba6..5d52146643372340cbb685e2c1490bc4495237ff 100644
--- a/etx4velo/pipeline/utils/plotutils/tracks.py
+++ b/etx4velo/pipeline/utils/plotutils/tracks.py
@@ -108,8 +108,8 @@ def plot_tracks(
     fig, mpl_axes = plt.subplots(1, len(list_axes), figsize=(8 * len(list_axes), 6))
     for mpl_ax, axes in zip(mpl_axes, list_axes):
         # plot all the hits
-        mpl_ax.set_xlabel(axes[0])
-        mpl_ax.set_ylabel(axes[1])
+        mpl_ax.set_xlabel(f"${axes[0]}$ [mm]")
+        mpl_ax.set_ylabel(f"${axes[1]}$ [mm]")
         mpl_ax.grid(color="grey", alpha=0.2)
 
         mpl_ax.scatter(
diff --git a/etx4velo/pipeline_configs/focal-loss-nopid-triplets-embedding-3-withspillover-d2max0.02.yaml b/etx4velo/pipeline_configs/focal-loss-nopid-triplets-embedding-3-withspillover-d2max0.02.yaml
index b8e447cbe1db64d04f5a1481540878f06e584c72..f5d02917444e8057e072a0a3baa65e3b59e6c7d2 100644
--- a/etx4velo/pipeline_configs/focal-loss-nopid-triplets-embedding-3-withspillover-d2max0.02.yaml
+++ b/etx4velo/pipeline_configs/focal-loss-nopid-triplets-embedding-3-withspillover-d2max0.02.yaml
@@ -2,9 +2,7 @@ common:
   experiment_name: focal-loss-nopid-triplets-embedding-3-withspillover-d2max0.02
   gpus: 1
   test_dataset_names:
-  # - minbias-sim10b-xdigi_v2.4_1496
   - minbias-sim10b-xdigi_v2.4_1498
-  # - minbias-sim10b-xdigi_v2.4_1500
   - minbias-sim10b-xdigi_v2.4_1480-1485
 
 
diff --git a/etx4velo/pipeline_configs/focal-loss-nopid-triplets-embedding-3-withspillover-new.yaml b/etx4velo/pipeline_configs/focal-loss-nopid-triplets-embedding-3-withspillover-new.yaml
index aedac0c2e8613fc18614ff4c1720633a0acc948e..88966c07424424d99cbb79505f86448db42841ca 100644
--- a/etx4velo/pipeline_configs/focal-loss-nopid-triplets-embedding-3-withspillover-new.yaml
+++ b/etx4velo/pipeline_configs/focal-loss-nopid-triplets-embedding-3-withspillover-new.yaml
@@ -1,16 +1,8 @@
 common:
   experiment_name: focal-loss-nopid-triplets-embedding-3-withspillover-new
   test_dataset_names:
-  # - minbias-sim10b-xdigi-nospillover_v2.1_98
-  # - minbias-sim10b-xdigi-nospillover_v2.1_99
-  # - bu2kspi-sim10aU1-xdigi_v2.3_48
-  # - bu2kstee-sim10aU1-xdigi_v2.2.2_500
-  - minbias-sim10b-xdigi_v2.4_1496
   - minbias-sim10b-xdigi_v2.4_1498
-  # - minbias-sim10b-xdigi_v2.4_1500
   - minbias-sim10b-xdigi_v2.4_1480-1485
-  # - smog2-digi_v2.3_430
-  # - PbPb-minbias-sim10aU1-xdigi_v2.4_702
 
 preprocessing:
   input_dir: /scratch/acorreia/minbias-sim10b-xdigi
diff --git a/etx4velo/plotfactory/plot_data_statistics.py b/etx4velo/plotfactory/plot_data_statistics.py
index 1fc4ab1f72e1cf247b644069f64880b837c433a3..fb770671bb16cb8ec5818aaf881f6adbf9778d3e 100644
--- a/etx4velo/plotfactory/plot_data_statistics.py
+++ b/etx4velo/plotfactory/plot_data_statistics.py
@@ -67,7 +67,7 @@ if __name__ == "__main__":
         series_n_true_hits_per_event,
         density=True,
         range=(min_range, max_range),
-        bins=100,
+        bins=70,
     )
     if has_noise:
         hist_n_fake_hits, _ = np.histogram(
@@ -108,9 +108,7 @@ if __name__ == "__main__":
             width=bin_widths,
             color="r",
             alpha=0.5,
-            label=(
-                f"Noise $\\left({prop_fake_hits_mean * 100:.1f} \\%\\right)$"
-            ),
+            label=(f"Noise $\\left({prop_fake_hits_mean * 100:.1f} \\%\\right)$"),
         )
     add_text(ax, ha="right", y=0.7)
     ax.legend()
@@ -130,7 +128,7 @@ if __name__ == "__main__":
     ax.set_xlabel("\\# reconstructible particles per event")
     ax.set_ylabel("Density")
     ax.grid(color="grey", alpha=0.2)
-    ax.hist(particle_counts_per_event, color="purple", bins=100)
+    ax.hist(particle_counts_per_event, color="purple", bins=70, range=(0, 400))
     add_text(ax, ha="right", va="top")
     save_fig(
         fig,
@@ -147,10 +145,10 @@ if __name__ == "__main__":
         .to_numpy()
     )
     fig, ax = plt.subplots(figsize=(8, 6))
-    ax.set_xlabel("\\# reconstructible particles in acceptance per event")
+    ax.set_xlabel("\\# reconstructible particles in acceptance\nper event")
     ax.set_ylabel("Density")
     ax.grid(color="grey", alpha=0.2)
-    ax.hist(particle_counts_per_event, color="purple", bins=100)
+    ax.hist(particle_counts_per_event, color="purple", bins=70, range=(0, 400))
     add_text(ax, ha="right", va="top")
     save_fig(
         fig,
diff --git a/etx4velo/plotfactory/plot_embedding_explanation.py b/etx4velo/plotfactory/plot_embedding_explanation.py
index f59d4a7da60bdb4a228129c6b35182d288cf521e..acc89cb142558c32d234fba39b373bfdaccc799f 100644
--- a/etx4velo/plotfactory/plot_embedding_explanation.py
+++ b/etx4velo/plotfactory/plot_embedding_explanation.py
@@ -80,10 +80,12 @@ def filter_edges_planes(
     ].reset_index(drop=True)
 
 
-def get_fig_ax(axes: typing.Tuple[str, str] = ("z", "x")) -> typing.Tuple[Figure, Axes]:
+def get_fig_ax(
+    axes: typing.Tuple[str, str] = ("z", "x"), unit: str = "mm"
+) -> typing.Tuple[Figure, Axes]:
     fig, ax = plt.subplots(figsize=(8, 6))
-    ax.set_xlabel(axes[0])
-    ax.set_ylabel(axes[1])
+    ax.set_xlabel(f"${axes[0]}$ [{unit}]")
+    ax.set_ylabel(f"${axes[1]}$ [{unit}]")
     ax.grid(color="grey", alpha=0.2)
     return fig, ax
 
diff --git a/etx4velo/snakefiles/matching.snake b/etx4velo/snakefiles/matching.snake
index 69b17ea8055c27b18bc5f0e968fabb77151556f7..b9c1d5be875853873bdf76398854b726a9db6ea9 100644
--- a/etx4velo/snakefiles/matching.snake
+++ b/etx4velo/snakefiles/matching.snake
@@ -90,5 +90,5 @@ rule matching_all:
         ),
         rules.report_evaluation_from_edges.output.report.format(
             experiment_name="focal-loss-nopid-triplets-embedding-3-withspillover-new",
-            test_dataset_name="minbias-sim10b-xdigi_v2.4_1496",
+            test_dataset_name="minbias-sim10b-xdigi_v2.4_1498",
         ),
diff --git a/etx4velo/snakefiles/snakeconfig.yaml b/etx4velo/snakefiles/snakeconfig.yaml
index 50d7aa2a5c76212935d042c8dfe3448df0d33a95..323704c5b9f7abf8dadb5b9e6c94191ef71329d4 100644
--- a/etx4velo/snakefiles/snakeconfig.yaml
+++ b/etx4velo/snakefiles/snakeconfig.yaml
@@ -2,7 +2,7 @@
 standatalone_test_dataset_names: ["minbias-sim10b-xdigi_v2.4_1498"]
 # Experiment names to use to generate figures unrelated to the training but
 # depend on the choice of an experiment
-main_experiment_names: []
+main_experiment_names: ["focal-loss-nopid-triplets-embedding-3-withspillover-new"]
 experiments:
   focal-loss-nopid-triplets-embedding-3-withspillover-new:
     # Sample used to choice the edge and triplet score cuts, and the maximal squared distance
@@ -11,12 +11,12 @@ experiments:
   focal-loss-nopid-triplets-embedding-3-withspillover-d2max0.02:
     choice: "minbias-sim10b-xdigi_v2.4_1498"
     steps: ["gnn", "track_building"]
-  focal-loss-nopid-triplets-embedding-6-withspillover:
-    choice: "minbias-sim10b-xdigi_v2.4_1498"
-    steps: ["embedding"]
-  focal-loss-nopid-triplets-embedding-6-withspillover-unsquared:
-    choice: "minbias-sim10b-xdigi_v2.4_1498"
-    steps: ["embedding"]
-  focal-loss-nopid-triplets-embedding-6-withspillover-nonorm:
-    choice: "minbias-sim10b-xdigi_v2.4_1498"
-    steps: ["embedding"]
+  # focal-loss-nopid-triplets-embedding-6-withspillover:
+  #   choice: "minbias-sim10b-xdigi_v2.4_1498"
+  #   steps: ["embedding"]
+  # focal-loss-nopid-triplets-embedding-6-withspillover-unsquared:
+  #   choice: "minbias-sim10b-xdigi_v2.4_1498"
+  #   steps: ["embedding"]
+  # focal-loss-nopid-triplets-embedding-6-withspillover-nonorm:
+  #   choice: "minbias-sim10b-xdigi_v2.4_1498"
+  #   steps: ["embedding"]
diff --git a/montetracko b/montetracko
index 0ddf2ece845f20f0cbd24188326e7746a1a6d400..bc04bae796ad9520254f03d6a66639f636e1ba67 160000
--- a/montetracko
+++ b/montetracko
@@ -1 +1 @@
-Subproject commit 0ddf2ece845f20f0cbd24188326e7746a1a6d400
+Subproject commit bc04bae796ad9520254f03d6a66639f636e1ba67