diff --git a/src/autoplex/auto/phonons/jobs.py b/src/autoplex/auto/phonons/jobs.py
index b379473d..d29ce513 100644
--- a/src/autoplex/auto/phonons/jobs.py
+++ b/src/autoplex/auto/phonons/jobs.py
@@ -791,6 +791,7 @@ def get_output(
     # TODO: potentially evaluation of imaginary modes
 
     rms_max_values = []  # get the largest rms in each fit
+
     for i in range(len(metrics[0])):
         rms_max_value = max(sublist[i]["benchmark_phonon_rmse"] for sublist in metrics)
         rms_max_values.append(rms_max_value)
diff --git a/tests/auto/phonons/test_jobs.py b/tests/auto/phonons/test_jobs.py
index 35bf0b3f..31b570f5 100644
--- a/tests/auto/phonons/test_jobs.py
+++ b/tests/auto/phonons/test_jobs.py
@@ -122,43 +122,9 @@ def test_get_output(clean_dir,test_dir,memory_jobstore):
     from jobflow import run_locally
 
     input_dict={"metrics": [[{"benchmark_phonon_rmse": 0.12230662063050536, "dft_imaginary_modes": True,
-                  "ml_imaginary_modes": False, "ml_model": "GAP", "mp_id": "test",
-                  "structure": {"@module": "pymatgen.core.structure", "@class": "Structure", "charge": 0, "lattice": {
-                      "matrix": [[5.527464055912056, 0.0, 3.3845955817373727e-16],
-                                 [8.888840143585662e-16, 5.527464055912056, 3.3845955817373727e-16],
-                                 [0.0, 0.0, 3.006687739088837]], "pbc": [True, True, True], "a": 5.527464055912056,
-                      "b": 5.527464055912056, "c": 3.006687739088837, "alpha": 90.0, "beta": 90.0,
-                      "gamma": 89.99999999999999, "volume": 91.86290621686962}, "properties": {}, "sites": [
-                      {"species": [{"element": "Sn", "occu": 1}], "abc": [0.5, 0.0, 0.25], "properties": {},
-                       "label": "Sn", "xyz": [2.763732027956028, 0.0, 0.7516719347722095]},
-                      {"species": [{"element": "Sn", "occu": 1}], "abc": [0.0, 0.0, 0.0], "properties": {},
-                       "label": "Sn", "xyz": [0.0, 0.0, 0.0]},
-                      {"species": [{"element": "Sn", "occu": 1}], "abc": [0.0, 0.5, 0.75], "properties": {},
-                       "label": "Sn", "xyz": [4.444420071792831e-16, 2.763732027956028, 2.255015804316628]},
-                      {"species": [{"element": "Sn", "occu": 1}], "abc": [0.5, 0.5, 0.5], "properties": {},
-                       "label": "Sn", "xyz": [2.7637320279560282, 2.763732027956028, 1.503343869544419]}]},
-                  "displacement": 0.01, "atomwise_regularization_parameter": 0.1,
-                  "soap_dict": {"delta": 1.0, "n_sparse": 6000}, "suffix": "full"}], [
+                  "ml_imaginary_modes": False}], [
                     {"benchmark_phonon_rmse": 0.08305510558730159, "dft_imaginary_modes": False,
-                     "ml_imaginary_modes": False, "ml_model": "GAP", "mp_id": "test2",
-                     "structure": {"@module": "pymatgen.core.structure", "@class": "Structure", "charge": 0,
-                                   "lattice": {"matrix": [[5.586266865017504, 0.0, 3.4206019177133026e-16],
-                                                          [8.983402272772745e-16, 5.586266865017504,
-                                                           3.4206019177133026e-16], [0.0, 0.0, 3.0386737788663782]],
-                                               "pbc": [True, True, True], "a": 5.586266865017504,
-                                               "b": 5.586266865017504, "c": 3.0386737788663782, "alpha": 90.0,
-                                               "beta": 90.0, "gamma": 89.99999999999999, "volume": 94.82600100373789},
-                                   "properties": {}, "sites": [
-                             {"species": [{"element": "Sn", "occu": 1}], "abc": [0.5, 0.0, 0.25], "properties": {},
-                              "label": "Sn", "xyz": [2.793133432508752, 0.0, 0.7596684447165948]},
-                             {"species": [{"element": "Sn", "occu": 1}], "abc": [0.0, 0.0, 0.0], "properties": {},
-                              "label": "Sn", "xyz": [0.0, 0.0, 0.0]},
-                             {"species": [{"element": "Sn", "occu": 1}], "abc": [0.0, 0.5, 0.75], "properties": {},
-                              "label": "Sn", "xyz": [4.491701136386372e-16, 2.793133432508752, 2.279005334149784]},
-                             {"species": [{"element": "Sn", "occu": 1}], "abc": [0.5, 0.5, 0.5], "properties": {},
-                              "label": "Sn", "xyz": [2.7931334325087525, 2.793133432508752, 1.5193368894331896]}]},
-                     "displacement": 0.01, "atomwise_regularization_parameter": 0.1,
-                     "soap_dict": {"delta": 1.0, "n_sparse": 6000}, "suffix": "full"}]]}
+                     "ml_imaginary_modes": False}]]}
 
     job_here=get_output(metrics=input_dict["metrics"])
 
@@ -166,6 +132,20 @@ def test_get_output(clean_dir,test_dir,memory_jobstore):
 
     responses[job_here.uuid][1].output["rms"] == pytest.approx(0.1223)
 
+    input_dict = {"metrics": [[{"benchmark_phonon_rmse": 0.12230662063050536, "dft_imaginary_modes": True,
+                                "ml_imaginary_modes": False}, {"benchmark_phonon_rmse": 0.15230662063050536, "dft_imaginary_modes": True,
+                                "ml_imaginary_modes": False}], [
+                                  {"benchmark_phonon_rmse": 0.08305510558730159, "dft_imaginary_modes": False,
+                                   "ml_imaginary_modes": False}, {"benchmark_phonon_rmse": 0.12230662063050536, "dft_imaginary_modes": True,
+                                "ml_imaginary_modes": False}]]}
+
+    job_here=get_output(metrics=input_dict["metrics"])
+
+    responses=run_locally(job_here)
+
+    responses[job_here.uuid][1].output["rms"] == pytest.approx(0.1223)
+
+
 def test_complete_benchmark(clean_dir, test_dir, memory_jobstore):
     from monty.serialization import loadfn
     from atomate2.common.schemas.phonons import PhononBSDOSDoc