diff --git a/fink_filters/ztf/filter_anomaly_notification/filter.py b/fink_filters/ztf/filter_anomaly_notification/filter.py
index a4fca10..c9a705f 100755
--- a/fink_filters/ztf/filter_anomaly_notification/filter.py
+++ b/fink_filters/ztf/filter_anomaly_notification/filter.py
@@ -14,7 +14,6 @@
 # limitations under the License.
 import pandas as pd
 import numpy as np
-
 from astropy import units as u
 from astropy.coordinates import SkyCoord
 
@@ -133,7 +132,7 @@ def anomaly_notification_(
     ...     df_proc = df.select(
     ...         'objectId', 'candidate.ra',
     ...         'candidate.dec', 'candidate.rb',
-    ...         f'anomaly_score{model}', 'timestamp')
+    ...         f'anomaly_score{model}', 'timestamp', 'candid')
     ...     df_out = anomaly_notification_(df_proc, send_to_tg=False,
     ...     send_to_slack=False, send_to_anomaly_base=True, model=model)
 
@@ -141,7 +140,7 @@ def anomaly_notification_(
     >>> df_proc = df.select(
     ...         'objectId', 'candidate.ra',
     ...         'candidate.dec', 'candidate.rb',
-    ...         'anomaly_score', 'timestamp')
+    ...         'anomaly_score', 'timestamp', 'candid')
     >>> pdf_anomalies = anomaly_notification_(df_proc, threshold=10,
     ...     send_to_tg=True, channel_id='@fink_test',
     ...     send_to_slack=False, channel_name=None)
@@ -161,7 +160,9 @@ def anomaly_notification_(
         cut_count = df_proc.count()
         if cut_count == 0:
             return pd.DataFrame()
-
+    df_proc = df_proc.filter(f"not isnan(anomaly_score{model})")
+    if df_proc.rdd.isEmpty():
+        return pd.DataFrame()
     # Compute the median for the night
     buf_df = df_proc.select(f"anomaly_score{model}")
     med = buf_df.approxQuantile(f"anomaly_score{model}", [0.5], 0.05)
@@ -242,6 +243,7 @@ def anomaly_notification_(
 {t5_}""".replace("\n", "  \n"),
             cutout,
             curve,
+            row.candid,
         ))
 
     init_msg = f"Median anomaly score overnight: {med}."
diff --git a/fink_filters/ztf/filter_anomaly_notification/filter_utils.py b/fink_filters/ztf/filter_anomaly_notification/filter_utils.py
index 59a2051..f8a8641 100755
--- a/fink_filters/ztf/filter_anomaly_notification/filter_utils.py
+++ b/fink_filters/ztf/filter_anomaly_notification/filter_utils.py
@@ -445,19 +445,19 @@ def load_to_anomaly_base(data, model, timeout=60):
                 tg_id_data = int(tg_id_data.replace('"', ""))
             except ValueError:
                 tg_id_data = "ND"
-        for ztf_id, text_data, cutout, curve in data:
+        for ztf_id, text_data, cutout, curve, candid_id in data:
             cutout.seek(0)
             curve.seek(0)
             files = {"image1": cutout, "image2": curve}
-            data = {"description": text_data}
-            params = {"ztf_id": ztf_id}
+            data_payload = {"description": text_data}
+            params = {"ztf_id": ztf_id, "candid_id": candid_id}
             headers = {"Authorization": f"Bearer {access_token}"}
             response = send_post_request_with_retry(
                 session=session,
                 url="https://anomaly.fink-broker.org:443/images/upload",
                 files=files,
                 params=params,
-                data=data,
+                data=data_payload,
                 headers=headers,
                 timeout=timeout,
                 source="upload_to_anomaly_base",
@@ -467,11 +467,14 @@ def load_to_anomaly_base(data, model, timeout=60):
             curve.seek(0)
             if tg_id_data == "ND":
                 continue
+            callback_anomaly = f"A_{candid_id}_{ztf_id}"
+            callback_not_anomaly = f"NA_{candid_id}_{ztf_id}"
+
             inline_keyboard = {
                 "inline_keyboard": [
                     [
-                        {"text": "Anomaly", "callback_data": f"A_{ztf_id}"},
-                        {"text": "Not anomaly", "callback_data": f"NA_{ztf_id}"},
+                        {"text": "Anomaly", "callback_data": callback_anomaly},
+                        {"text": "Not anomaly", "callback_data": callback_not_anomaly},
                     ]
                 ]
             }