diff --git a/matbench_discovery/data.py b/matbench_discovery/data.py
index 5bd4a676..7a8e5ff0 100644
--- a/matbench_discovery/data.py
+++ b/matbench_discovery/data.py
@@ -423,8 +423,8 @@ class Model(Files, base_dir=f"{ROOT}/models"):
     cgcnn_p = "cgcnn/cgcnn+p.yml"
 
     # DeepMD-DPA3 models
-    dpa3_v1_mptrj = "deepmd_dpa3/dpa3-v1-mptrj.yml"
-    dpa3_v1_openlam = "deepmd_dpa3/dpa3-v1-openlam.yml"
+    dpa3_v1_mptrj = "deepmd/dpa3-v1-mptrj.yml"
+    dpa3_v1_openlam = "deepmd/dpa3-v1-openlam.yml"
 
     # original M3GNet straight from publication, not re-trained
     m3gnet = "m3gnet/m3gnet.yml"
@@ -453,7 +453,7 @@ class Model(Files, base_dir=f"{ROOT}/models"):
     gnome = "gnome/gnome.yml"
 
     # MatterSim
-    mattersim = "mattersim/mattersim-v1.yml"
+    mattersim_v1_5m = "mattersim/mattersim-v1-5m.yml"
 
     # ORB
     orb = "orb/orb.yml"
@@ -530,17 +530,17 @@ def geo_opt_path(self) -> str | None:
         return f"{ROOT}/{rel_path}"
 
     @property
-    def phonons_path(self) -> str | None:
+    def kappa_103_path(self) -> str | None:
         """File path associated with the file URL if it exists, otherwise
         download the file first, then return the path.
         """
         phonons_metrics = self.metrics.get("phonons", {})
         if phonons_metrics in ("not available", "not applicable"):
             return None
-        rel_path = phonons_metrics.get("pred_file")
+        rel_path = phonons_metrics.get("kappa_103", {}).get("pred_file")
         if not rel_path:
             raise ValueError(
-                f"metrics.phonons.pred_file not found in {self.rel_path!r}"
+                f"metrics.phonons.kappa_103.pred_file not found in {self.rel_path!r}"
             )
         return f"{ROOT}/{rel_path}"
 
diff --git a/matbench_discovery/metrics/phonons.py b/matbench_discovery/metrics/phonons.py
index c1a7a5b6..24dc47ac 100644
--- a/matbench_discovery/metrics/phonons.py
+++ b/matbench_discovery/metrics/phonons.py
@@ -53,9 +53,6 @@ def calc_kappa_metrics_from_dfs(
         - DFT_kappa_tot_avg: Reference DFT conductivity values
     """
     # Remove precomputed columns
-    cols_to_remove = [Key.srd, Key.sre, Key.srme, MbdKey.true_kappa_tot_avg]
-    df_pred = df_pred.drop(columns=cols_to_remove, errors="ignore")
-
     df_pred[MbdKey.kappa_tot_avg] = df_pred[MbdKey.kappa_tot_rta].map(
         calculate_kappa_avg
     )
@@ -102,7 +99,7 @@ def calculate_kappa_avg(kappa: np.ndarray) -> np.ndarray:
         any NaN values or if the calculation fails. For multiple temperatures,
         returns an array of averages.
     """
-    if np.any(np.isnan(kappa)):
+    if np.any(pd.isna(kappa)):
         return np.array([np.nan])
     try:
         return np.asarray(kappa)[..., :3].mean(axis=-1)
@@ -222,7 +219,7 @@ def calc_kappa_srme(kappas_pred: pd.Series, kappas_true: pd.Series) -> np.ndarra
                 f"Neither mode_kappa_tot_avg, mode_kappa_tot nor individual kappa\n"
                 f"components found in {label}, got\n{keys}"
             )
-        mode_kappa_tot_avgs[label] = kappas
+        mode_kappa_tot_avgs[label] = np.asarray(kappas)
 
     # calculating microscopic error for all temperatures
     microscopic_error = (
diff --git a/matbench_discovery/phonons/__init__.py b/matbench_discovery/phonons/__init__.py
index 682da7a6..1915e6e2 100644
--- a/matbench_discovery/phonons/__init__.py
+++ b/matbench_discovery/phonons/__init__.py
@@ -1,8 +1,17 @@
 """This package contains phonon-related functionality."""
 
+from typing import Final
+
 import numpy as np
 import pandas as pd
 
+# q-point mesh (which phonon modes to sample) based on international space group number
+spg_num_q_mesh_map: Final[dict[int, tuple[int, int, int]]] = {
+    225: (19, 19, 19),  # rocksalt
+    186: (19, 19, 15),  # wurtzite
+    216: (19, 19, 19),  # zincblende
+}
+
 
 def check_imaginary_freqs(frequencies: np.ndarray, threshold: float = -0.01) -> bool:
     """Check if frequencies are imaginary.
diff --git a/matbench_discovery/phonons/thermal_conductivity.py b/matbench_discovery/phonons/thermal_conductivity.py
index 7ec68740..a8500e61 100644
--- a/matbench_discovery/phonons/thermal_conductivity.py
+++ b/matbench_discovery/phonons/thermal_conductivity.py
@@ -9,6 +9,7 @@
 """
 
 import warnings
+from collections.abc import Sequence
 from copy import deepcopy
 from typing import Any
 
@@ -108,17 +109,25 @@ def calculate_fc3_set(
 
 def init_phono3py(
     atoms: Atoms,
-    symprec: float = 1e-5,
+    *,
+    fc2_supercell: np.ndarray,
+    fc3_supercell: np.ndarray,
+    q_point_mesh: tuple[int, int, int] = (20, 20, 20),
     displacement_distance: float = 0.03,
+    symprec: float = 1e-5,
     **kwargs: Any,
 ) -> Phono3py:
     """Initialize Phono3py object from ASE Atoms.
 
     Args:
         atoms (Atoms): ASE Atoms object to initialize from.
-        symprec (float): Symmetry precision for finding space group. Defaults to 1e-5.
+        fc2_supercell (np.ndarray): Supercell matrix for 2nd order force constants.
+        fc3_supercell (np.ndarray): Supercell matrix for 3rd order force constants.
+        q_point_mesh (tuple[int, int, int]): Mesh size for q-point sampling. Defaults
+            to (20, 20, 20).
         displacement_distance (float): Displacement distance for force calculations.
             Defaults to 0.03.
+        symprec (float): Symmetry precision for finding space group. Defaults to 1e-5.
         **kwargs (Any): Passed to Phono3py constructor.
 
     Returns:
@@ -127,21 +136,16 @@ def init_phono3py(
     Raises:
         ValueError: If required metadata is missing from atoms.info
     """
-    formula = atoms.get_chemical_formula(mode="metal")
-    for key in ("fc2_supercell", "fc3_supercell", "q_mesh"):
-        if key not in atoms.info:
-            raise ValueError(f"{formula} {key=} not found in {atoms.info=}")
-
     unit_cell = PhonopyAtoms(atoms.symbols, cell=atoms.cell, positions=atoms.positions)
     ph3 = Phono3py(
         unitcell=unit_cell,
-        supercell_matrix=atoms.info["fc3_supercell"],
-        phonon_supercell_matrix=atoms.info["fc2_supercell"],
+        supercell_matrix=fc3_supercell,
+        phonon_supercell_matrix=fc2_supercell,
         primitive_matrix="auto",
         symprec=symprec,
         **kwargs,
     )
-    ph3.mesh_numbers = atoms.info["q_mesh"]
+    ph3.mesh_numbers = q_point_mesh
 
     ph3.generate_displacements(distance=displacement_distance)
 
@@ -207,7 +211,7 @@ def load_force_sets(
 
 def calculate_conductivity(
     ph3: Phono3py,
-    temperatures: list[float],
+    temperatures: Sequence[float],
     boundary_mfp: float = 1e6,
     mode_kappa_thresh: float = 1e-6,
     **kwargs: Any,
diff --git a/models/chgnet/chgnet.yml b/models/chgnet/chgnet.yml
index f1b72571..0d4a0807 100644
--- a/models/chgnet/chgnet.yml
+++ b/models/chgnet/chgnet.yml
@@ -65,7 +65,10 @@ notes:
 
 metrics:
   phonons:
-    κ_SRME: 1.717
+    kappa_103:
+      κ_SRME: 1.717
+      pred_file: models/chgnet/chgnet-0.3.0/2024-11-09-kappa-103-FIRE-fmax=1e-4-symprec=1e-5.json.gz
+      pred_file_url: https://figshare.com/ndownloader/files/52134857
   geo_opt:
     pred_file: models/chgnet/chgnet-0.3.0/2023-12-21-wbm-geo-opt.json.gz
     pred_file_url: https://figshare.com/ndownloader/files/52061999
diff --git a/models/deepmd_dpa3/dpa3-v1-mptrj.yml b/models/deepmd/dpa3-v1-mptrj.yml
similarity index 90%
rename from models/deepmd_dpa3/dpa3-v1-mptrj.yml
rename to models/deepmd/dpa3-v1-mptrj.yml
index ad6c3a81..ed61ccb0 100644
--- a/models/deepmd_dpa3/dpa3-v1-mptrj.yml
+++ b/models/deepmd/dpa3-v1-mptrj.yml
@@ -88,20 +88,22 @@ notes:
     Designed as a large atomic model (LAM), DPA3 is tailored to integrate and simultaneously train on datasets from various disciplines, encompassing diverse chemical and materials systems across different research domains.
     Its model design ensures exceptional fitting accuracy and robust generalization both within and beyond the training domain.
     Furthermore, DPA3 maintains energy conservation and respects the physical symmetries of the potential energy surface, making it a dependable tool for a wide range of scientific applications.
+
 metrics:
   phonons:
-    pred_file: models/deepmd_dpa3/dpa3-v1-mptrj/2025-01-10-kappa-103.json.gz
-    pred_file_url: https://figshare.com/ndownloader/files/52057901
-    κ_SRME: 0.964
+    kappa_103:
+      κ_SRME: 0.964
+      pred_file: models/deepmd/dpa3-v1-mptrj/2025-01-10-kappa-103-FIRE-dist=0.01-fmax=1e-4-symprec=1e-5.json.gz
+      pred_file_url: https://figshare.com/ndownloader/files/52134860
   geo_opt:
-    pred_file: models/deepmd_dpa3/dpa3-v1-mptrj/2025-01-10-wbm-geo-opt.json.gz
+    pred_file: models/deepmd/dpa3-v1-mptrj/2025-01-10-wbm-geo-opt.json.gz
     pred_col: dp_structure
-    pred_file_url:
+    pred_file_url: https://figshare.com/ndownloader/files/52134974
     symprec=1e-5:
-      analysis_file: models/deepmd_dpa3/dpa3-v1-mptrj/2025-01-10-wbm-geo-opt-symprec=1e-5.csv.gz
+      analysis_file: models/deepmd/dpa3-v1-mptrj/2025-01-10-wbm-geo-opt-symprec=1e-5.csv.gz
       analysis_file_url: https://figshare.com/ndownloader/files/52059431
   discovery:
-    pred_file: models/deepmd_dpa3/dpa3-v1-mptrj/2025-01-10-wbm-IS2RE.csv.gz
+    pred_file: models/deepmd/dpa3-v1-mptrj/2025-01-10-wbm-IS2RE.csv.gz
     pred_file_url: https://figshare.com/ndownloader/files/52057529
     pred_col: e_form_per_atom_dp
     full_test_set:
diff --git a/models/deepmd_dpa3/dpa3-v1-openlam.yml b/models/deepmd/dpa3-v1-openlam.yml
similarity index 91%
rename from models/deepmd_dpa3/dpa3-v1-openlam.yml
rename to models/deepmd/dpa3-v1-openlam.yml
index a9ad68ee..02db2a15 100644
--- a/models/deepmd_dpa3/dpa3-v1-openlam.yml
+++ b/models/deepmd/dpa3-v1-openlam.yml
@@ -100,20 +100,22 @@ notes:
     Designed as a large atomic model (LAM), DPA3 is tailored to integrate and simultaneously train on datasets from various disciplines, encompassing diverse chemical and materials systems across different research domains.
     Its model design ensures exceptional fitting accuracy and robust generalization both within and beyond the training domain.
     Furthermore, DPA3 maintains energy conservation and respects the physical symmetries of the potential energy surface, making it a dependable tool for a wide range of scientific applications.
+
 metrics:
   phonons:
-    pred_file: models/deepmd_dpa3/dpa3-v1-openlam/2025-01-10-kappa-103.json.gz
-    pred_file_url: https://figshare.com/ndownloader/files/52057904
-    κ_SRME: 0.741
+    kappa_103:
+      κ_SRME: 0.741
+      pred_file: models/deepmd/dpa3-v1-openlam/2025-01-10-kappa-103-FIRE-dist=0.01-fmax=1e-4-symprec=1e-5.json.gz
+      pred_file_url: https://figshare.com/ndownloader/files/52134863
   geo_opt:
-    pred_file: models/deepmd_dpa3/dpa3-v1-openlam/2025-01-10-wbm-geo-opt.json.gz
+    pred_file: models/deepmd/dpa3-v1-openlam/2025-01-10-wbm-geo-opt.json.gz
     pred_col: dp_structure
-    pred_file_url:
+    pred_file_url: https://figshare.com/ndownloader/files/52135358
     symprec=1e-5:
-      analysis_file: models/deepmd_dpa3/dpa3-v1-openlam/2025-01-10-wbm-geo-opt-symprec=1e-5.csv.gz
+      analysis_file: models/deepmd/dpa3-v1-openlam/2025-01-10-wbm-geo-opt-symprec=1e-5.csv.gz
       analysis_file_url: https://figshare.com/ndownloader/files/52059434
   discovery:
-    pred_file: models/deepmd_dpa3/dpa3-v1-openlam/2025-01-10-wbm-IS2RE.csv.gz
+    pred_file: models/deepmd/dpa3-v1-openlam/2025-01-10-wbm-IS2RE.csv.gz
     pred_file_url: https://figshare.com/ndownloader/files/52057532
     pred_col: e_form_per_atom_dp
     full_test_set:
diff --git a/models/deepmd_dpa3/join_dpa3_preds.py b/models/deepmd/join_dpa3_preds.py
similarity index 100%
rename from models/deepmd_dpa3/join_dpa3_preds.py
rename to models/deepmd/join_dpa3_preds.py
diff --git a/models/deepmd_dpa3/readme.md b/models/deepmd/readme.md
similarity index 100%
rename from models/deepmd_dpa3/readme.md
rename to models/deepmd/readme.md
diff --git a/models/deepmd_dpa3/test_dpa3.py b/models/deepmd/test_dpa3.py
similarity index 100%
rename from models/deepmd_dpa3/test_dpa3.py
rename to models/deepmd/test_dpa3.py
diff --git a/models/eqV2/eqV2-m-omat-mp-salex.yml b/models/eqV2/eqV2-m-omat-mp-salex.yml
index dcdadf5a..24a83ba6 100644
--- a/models/eqV2/eqV2-m-omat-mp-salex.yml
+++ b/models/eqV2/eqV2-m-omat-mp-salex.yml
@@ -85,6 +85,11 @@ notes:
     Training was done by fine-tuning a model pretrained for 2 epochs on the OMat24 dataset.
 
 metrics:
+  phonons:
+    kappa_103:
+      κ_SRME: 1.717
+      pred_file: models/eqV2/eqV2-m-omat-mp-salex/2024-11-09-kappa-103-FIRE-dist=0.01-fmax=1e-4-symprec=1e-5.json.gz
+      pred_file_url: https://figshare.com/ndownloader/files/52134893
   geo_opt:
     pred_file: models/eqV2/eqV2-m-omat-mp-salex/2024-10-18-wbm-geo-opt.json.gz
     pred_file_url: https://figshare.com/ndownloader/files/51607436
diff --git a/models/eqV2/eqV2-s-dens-mp.yml b/models/eqV2/eqV2-s-dens-mp.yml
index a2fe5a77..d02dd0a3 100644
--- a/models/eqV2/eqV2-s-dens-mp.yml
+++ b/models/eqV2/eqV2-s-dens-mp.yml
@@ -88,7 +88,10 @@ notes:
 
 metrics:
   phonons:
-    κ_SRME: 1.665 # eqV2 S without denoising (no DeNS) achieves slightly worse κ_SRME=1.772
+    kappa_103:
+      κ_SRME: 1.665 # eqV2 S without denoising (no DeNS) achieves slightly worse κ_SRME=1.772
+      pred_file: TODO find this file or regenerate it
+      pred_file_url: https://figshare.com/TODO add this URL
   geo_opt:
     pred_file: models/eqV2/eqV2-s-dens-mp/2024-10-18-wbm-geo-opt.json.gz
     pred_file_url: https://figshare.com/ndownloader/files/52062392
diff --git a/models/gnome/gnome.yml b/models/gnome/gnome.yml
index 9c36a2dc..e5df3b5a 100644
--- a/models/gnome/gnome.yml
+++ b/models/gnome/gnome.yml
@@ -61,10 +61,8 @@ notes:
   Missing Preds: According to the authors, the 1734 missing WBM predictions are mostly due out-of-memory (OOM) errors. The model was evaluated on A100s but without neighbor lists. The plan is to backfill the missing predictions once H100s are available or neighbor list implementation goes live.
 
 metrics:
-  geo_opt:
-    pred_file: # not (yet) shared by authors
-    pred_file_url:
-    pred_col:
+  phonons: not available # model is closed source, original GnoME submission predates phonon tasks and DeepMind did not resubmit later
+  geo_opt: not available # author's declined to share model-relaxed structures and can't be reproduced without model access
   discovery:
     pred_file: models/gnome/2023-11-01-gnome-50076332-wbm-IS2RE.csv.gz
     pred_file_url: https://figshare.com/ndownloader/files/52057556
diff --git a/models/grace/grace2l-r6.yml b/models/grace/grace2l-r6.yml
index 66005270..8bbd8a8e 100644
--- a/models/grace/grace2l-r6.yml
+++ b/models/grace/grace2l-r6.yml
@@ -51,7 +51,10 @@ hyperparams:
 
 metrics:
   phonons:
-    κ_SRME: 0.525 # https://github.com/MPA2suite/k_SRME/pull/11/files
+    kappa_103:
+      κ_SRME: 0.525 # https://github.com/MPA2suite/k_SRME/pull/11/files
+      pred_file: models/grace/grace2l_r6/2024-11-20-kappa-103-FIRE-fmax=1e-4-symprec=1e-5.json.gz
+      pred_file_url: https://figshare.com/ndownloader/files/52134896
   geo_opt:
     pred_file: models/grace/grace2l_r6/2024-11-11-relaxed-structures.json.gz
     pred_file_url: https://figshare.com/ndownloader/files/52062590
diff --git a/models/m3gnet/m3gnet.yml b/models/m3gnet/m3gnet.yml
index 1ed99909..48d98022 100644
--- a/models/m3gnet/m3gnet.yml
+++ b/models/m3gnet/m3gnet.yml
@@ -55,7 +55,10 @@ notes:
 
 metrics:
   phonons:
-    κ_SRME: 1.412
+    kappa_103:
+      κ_SRME: 1.412
+      pred_file: models/m3gnet/m3gnet-matgl-mp-2021-2-8-pes/2024-11-09-kappa-103-FIRE-dist=0.01-fmax=1e-4-symprec=1e-5.json.gz
+      pred_file_url: https://figshare.com/ndownloader/files/52134866
   geo_opt:
     pred_file: models/m3gnet/m3gnet-tf-manual-sampling/2023-06-01-wbm-geo-opt.json.gz
     pred_file_url: https://figshare.com/ndownloader/files/52062011
diff --git a/models/m3gnet/test_m3gnet_discovery.py b/models/m3gnet/test_m3gnet_discovery.py
index b79ce2e6..897510c2 100644
--- a/models/m3gnet/test_m3gnet_discovery.py
+++ b/models/m3gnet/test_m3gnet_discovery.py
@@ -74,11 +74,13 @@
 if slurm_array_task_count > 1:
     df_in = np.array_split(df_in, slurm_array_task_count)[slurm_array_task_id - 1]
 
-checkpoint = None
 if model_type == "direct":
     checkpoint = f"{ROOT}/models/{model_name}/2023-05-26-DI-DFTstrictF10-TTRS-128U-442E"
-if model_type == "ms":
+elif model_type == "manual-sampling":
     checkpoint = f"{ROOT}/models/{model_name}/2023-05-26-MS-DFTstrictF10-128U-154E"
+else:
+    raise ValueError(f"{model_type=} not supported")
+
 relax_results: dict[str, dict[str, Any]] = {}
 m3gnet = Relaxer(potential=checkpoint)  # load pre-trained M3GNet model
 
diff --git a/models/mace/calc_kappa_mace_ray_parallelized.py b/models/mace/calc_kappa_mace_ray_parallelized.py
index 0aefa9a9..922e9e17 100644
--- a/models/mace/calc_kappa_mace_ray_parallelized.py
+++ b/models/mace/calc_kappa_mace_ray_parallelized.py
@@ -31,6 +31,7 @@
 from matbench_discovery.phonons import thermal_conductivity as ltc
 
 if TYPE_CHECKING:
+    from ase.filters import Filter
     from ase.optimize.optimize import Optimizer
 
 module_dir = os.path.dirname(__file__)
@@ -43,6 +44,7 @@
 def calc_kappa_for_structure(
     *,  # force keyword-only arguments
     atoms: Atoms,
+    displacement_distance: float,
     checkpoint: str,
     temperatures: list[float],
     ase_optimizer: str,
@@ -60,7 +62,8 @@ def calc_kappa_for_structure(
     """Predict ML kappa for single structure with ray.
 
     Args:
-        atoms (Atoms): Input structure
+        atoms (Atoms): ASE Atoms object with fc2_supercell, fc3_supercell,
+            q_point_mesh keys in its info dict.
         calc (Calculator): ASE calculator
         temperatures (list[float]): Which temperatures to calculate kappa at in Kelvin
         ase_optimizer (str): ASE optimizer to use
@@ -88,21 +91,20 @@ def calc_kappa_for_structure(
     # Create a deep copy of the atoms object to avoid ray read-only issues
     atoms = atoms.copy()
     # Ensure arrays are writable
-    atoms.arrays = {k: v.copy() for k, v in atoms.arrays.items()}
+    atoms.arrays = {key: val.copy() for key, val in atoms.arrays.items()}
 
     mat_id = atoms.info[Key.mat_id]
     init_info = deepcopy(atoms.info)
     mat_name = atoms.info["name"]
-    info_dict = {
+    info_dict: dict[str, Any] = {
         "name": mat_name,
         "errors": [],
         "error_traceback": [],
     }
 
-    filter_cls: type[ExpCellFilter | FrechetCellFilter] = {
-        "frechet": FrechetCellFilter,
-        "exp": ExpCellFilter,
-    }[ase_filter]
+    filter_cls: Filter = {"frechet": FrechetCellFilter, "exp": ExpCellFilter}[
+        ase_filter
+    ]
 
     optim_cls: type[Optimizer] = {"FIRE": FIRE, "LBFGS": LBFGS}[ase_optimizer]
 
@@ -124,7 +126,7 @@ def calc_kappa_for_structure(
                 filtered_atoms = filter_cls(atoms)
 
             optimizer = optim_cls(
-                filtered_atoms, logfile=f"{out_dir}/relax_{task_id}.log"
+                filtered_atoms, logfile=f"{out_dir}/relaxations/{task_id}.log"
             )
             optimizer.run(fmax=force_max, steps=max_steps)
 
@@ -148,13 +150,20 @@ def calc_kappa_for_structure(
     except Exception as exc:
         warnings.warn(f"Failed to relax {mat_name=}, {mat_id=}: {exc!r}", stacklevel=2)
         traceback.print_exc()
-        info_dict["errors"].append(f"RelaxError: {exc!r}")
-        info_dict["error_traceback"].append(traceback.format_exc())
+        info_dict["errors"] += [f"RelaxError: {exc!r}"]
+        info_dict["error_traceback"] += [traceback.format_exc()]
         return mat_id, info_dict | relax_dict, None
 
     # Calculation of force sets
     try:
-        ph3 = ltc.init_phono3py(atoms, symprec=symprec)
+        ph3 = ltc.init_phono3py(
+            atoms,
+            fc2_supercell=atoms.info["fc2_supercell"],
+            fc3_supercell=atoms.info["fc3_supercell"],
+            q_point_mesh=atoms.info["q_point_mesh"],
+            displacement_distance=displacement_distance,
+            symprec=symprec,
+        )
 
         ph3, fc2_set, freqs = ltc.get_fc2_and_freqs(
             ph3, calculator=calc, pbar_kwargs={"disable": True}
@@ -186,8 +195,8 @@ def calc_kappa_for_structure(
     except Exception as exc:
         warnings.warn(f"Failed to calculate force sets {mat_id}: {exc!r}", stacklevel=2)
         traceback.print_exc()
-        info_dict["errors"].append(f"ForceConstantError: {exc!r}")
-        info_dict["error_traceback"].append(traceback.format_exc())
+        info_dict["errors"] += [f"ForceConstantError: {exc!r}"]
+        info_dict["error_traceback"] += [traceback.format_exc()]
         return mat_id, info_dict | relax_dict, force_results
 
     # Calculation of conductivity
@@ -195,7 +204,6 @@ def calc_kappa_for_structure(
         ph3, kappa_dict, _cond = ltc.calculate_conductivity(
             ph3, temperatures=temperatures
         )
-        print(f"{kappa_dict=}")
         return mat_id, info_dict | relax_dict | freqs_dict | kappa_dict, force_results
 
     except Exception as exc:
@@ -203,8 +211,8 @@ def calc_kappa_for_structure(
             f"Failed to calculate conductivity {mat_id}: {exc!r}", stacklevel=2
         )
         traceback.print_exc()
-        info_dict["errors"].append(f"ConductivityError: {exc!r}")
-        info_dict["error_traceback"].append(traceback.format_exc())
+        info_dict["errors"] += [f"ConductivityError: {exc!r}"]
+        info_dict["error_traceback"] += [traceback.format_exc()]
         return mat_id, info_dict | relax_dict | freqs_dict, force_results
 
 
@@ -216,7 +224,7 @@ def main() -> None:
     ase_optimizer: Literal["FIRE", "LBFGS", "BFGS"] = "FIRE"
     ase_filter: Literal["frechet", "exp"] = "frechet"
     max_steps = 300
-    force_max = 1e-4  # Run until the forces are smaller than this in eV/A
+    fmax = 1e-4  # Run until the forces are smaller than this in eV/A
 
     # Symmetry parameters
     symprec = 1e-5  # symmetry precision for enforcing relaxation and conductivity calcs
@@ -272,7 +280,11 @@ def main() -> None:
     checkpoint = f"https://github.com/ACEsuit/mace-mp/releases/download/mace_omat_0/{model_name}.model"
 
     task_type = "LTC"  # lattice thermal conductivity
-    job_name = f"phononDB-{task_type}-{ase_optimizer}_force{force_max}_sym{symprec}"
+    displacement_distance = 0.01
+    job_name = (
+        f"phononDB-{task_type}-{ase_optimizer}-dist={displacement_distance}-"
+        f"{fmax=}-{symprec=}"
+    )
     out_dir = os.getenv(
         "SBATCH_OUTPUT", f"{module_dir}/{model_name}/{today}-{job_name}"
     )
@@ -289,7 +301,7 @@ def main() -> None:
         ase_optimizer=ase_optimizer,
         ase_filter=ase_filter,
         max_steps=max_steps,
-        force_max=force_max,
+        force_max=fmax,
         symprec=symprec,
         enforce_relax_symm=enforce_relax_symm,
         conductivity_broken_symm=conductivity_broken_symm,
@@ -307,13 +319,13 @@ def main() -> None:
     futures = [
         calc_kappa_for_structure.remote(
             atoms=atoms,
-            # calc=calc,
+            displacement_distance=displacement_distance,
             checkpoint=checkpoint,
             temperatures=temperatures,
             ase_optimizer=ase_optimizer,
             ase_filter=ase_filter,
             max_steps=max_steps,
-            force_max=force_max,
+            force_max=fmax,
             symprec=symprec,
             enforce_relax_symm=enforce_relax_symm,
             conductivity_broken_symm=conductivity_broken_symm,
diff --git a/models/mace/mace-mp-0.yml b/models/mace/mace-mp-0.yml
index a0d54942..2c1ec232 100644
--- a/models/mace/mace-mp-0.yml
+++ b/models/mace/mace-mp-0.yml
@@ -70,7 +70,10 @@ notes:
 
 metrics:
   phonons:
-    κ_SRME: 0.647
+    kappa_103:
+      κ_SRME: 0.647
+      pred_file: models/mace/mace-mp-0/2024-11-09-kappa-103-FIRE-dist=0.01-fmax=1e-4-symprec=1e-5.json.gz
+      pred_file_url: https://figshare.com/ndownloader/files/52134872
   geo_opt:
     pred_file: models/mace/mace-mp-0/2023-12-11-wbm-IS2RE-FIRE.json.gz
     pred_file_url: https://figshare.com/ndownloader/files/52062020
diff --git a/models/mace/mace-mpa-0.yml b/models/mace/mace-mpa-0.yml
index 30a4fe29..7dc79d6d 100644
--- a/models/mace/mace-mpa-0.yml
+++ b/models/mace/mace-mpa-0.yml
@@ -69,10 +69,13 @@ notes:
 
 metrics:
   phonons:
-    κ_SRME: 0.412
+    kappa_103:
+      κ_SRME: 0.412
+      pred_file: models/mace/mace-mpa-0/2024-11-25-kappa-103-FIRE-dist=0.01-fmax=1e-4-symprec=1e-5.json.gz
+      pred_file_url: https://figshare.com/ndownloader/files/52134875
   geo_opt:
     pred_file: models/mace/mace-mpa-0/2024-12-09-wbm-IS2RE-FIRE.json.gz
-    pred_file_url:
+    pred_file_url: https://figshare.com/TODO add pred file URL
     pred_col: mace_structure
     symprec=1e-2:
       rmsd: 0.0142 # Å
@@ -82,6 +85,7 @@ metrics:
       symmetry_increase: 0.1231 # fraction
       n_structures: 256963 # count
       analysis_file: TODO add analysis file
+      analysis_file_url: https://figshare.com/TODO add analysis file URL
     symprec=1e-5:
       rmsd: 0.0142 # Å
       n_sym_ops_mae: 1.8808 # unitless
@@ -90,6 +94,7 @@ metrics:
       symmetry_increase: 0.2306 # fraction
       n_structures: 256963 # count
       analysis_file: TODO add analysis file
+      analysis_file_url: https://figshare.com/TODO add analysis file URL
   discovery:
     pred_file: models/mace/mace-mpa-0/2024-12-09-wbm-IS2RE-FIRE.csv.gz
     pred_file_url: https://figshare.com/ndownloader/files/52057541
diff --git a/models/mattersim/mattersim-v1.yml b/models/mattersim/mattersim-v1-5m.yml
similarity index 92%
rename from models/mattersim/mattersim-v1.yml
rename to models/mattersim/mattersim-v1-5m.yml
index c40f02b2..ff2fc8bf 100644
--- a/models/mattersim/mattersim-v1.yml
+++ b/models/mattersim/mattersim-v1-5m.yml
@@ -1,5 +1,5 @@
-model_name: MatterSim-v1
-model_key: mattersim-v1
+model_name: MatterSim v1 5M
+model_key: mattersim-v1-5m
 model_version: v1.0.0
 matbench_discovery_version: 1.0.0
 date_added: "2024-12-16"
@@ -120,12 +120,15 @@ notes:
     - newly generated structures and MD trajectories
 
 metrics:
-  phonons: # https://github.com/MPA2suite/k_SRME/pull/13
-    κ_SRME: 0.574 # dimensionless
+  phonons:
+    kappa_103: # https://github.com/MPA2suite/k_SRME/pull/13
+      κ_SRME: 0.574 # dimensionless
+      pred_file: models/mattersim/mattersim-v1-5m/2024-12-09-kappa-103-FIRE-dist=0.01-fmax=1e-4-symprec=1e-5.json.gz
+      pred_file_url: https://figshare.com/ndownloader/files/52134884
   geo_opt:
-    pred_file: models/mattersim/mattersim-v1-5M/2024-12-19-relaxed-structures.json.gz
+    pred_file: models/mattersim/mattersim-v1-5M/2024-12-19-wbm-geo-opt.json.gz
     pred_file_url: https://figshare.com/ndownloader/files/52062176
-    pred_col:
+    pred_col: mattersim_structure
   discovery:
     pred_file: models/mattersim/mattersim-v1-5M/2024-12-16-wbm-IS2RE.csv.gz
     # the original Graphormer-based replaced the M3GNet-based MatterSim on the leaderboard
diff --git a/models/orb/orb-mptrj.yml b/models/orb/orb-mptrj.yml
index 15156781..d33906da 100644
--- a/models/orb/orb-mptrj.yml
+++ b/models/orb/orb-mptrj.yml
@@ -74,7 +74,10 @@ notes:
 
 metrics:
   phonons:
-    κ_SRME: 1.725
+    kappa_103:
+      κ_SRME: 1.725
+      pred_file: models/orb/orbff-mptrj-v2/2024-11-09-kappa-103-FIRE-dist=0.01-fmax=1e-4-symprec=1e-5.json.gz
+      pred_file_url: https://figshare.com/ndownloader/files/52134890
   geo_opt:
     pred_file: models/orb/orbff-mptrj-v2/2024-10-14-wbm-geo-opt.json.gz
     pred_file_url: https://figshare.com/ndownloader/files/52062317
diff --git a/models/orb/orb.yml b/models/orb/orb.yml
index 20872800..808f85e0 100644
--- a/models/orb/orb.yml
+++ b/models/orb/orb.yml
@@ -74,7 +74,10 @@ notes:
 
 metrics:
   phonons:
-    κ_SRME: 1.732
+    kappa_103:
+      κ_SRME: 1.732
+      pred_file: models/orb/orbff-v2/2024-11-09-kappa-103-FIRE-dist=0.01-fmax=1e-4-symprec=1e-5.json.gz
+      pred_file_url: https://figshare.com/ndownloader/files/52134887
   geo_opt:
     pred_file: models/orb/orbff-v2/2024-10-11-wbm-geo-opt.json.gz
     pred_file_url: https://figshare.com/ndownloader/files/52062194
diff --git a/models/sevennet/sevennet-0.yml b/models/sevennet/sevennet-0.yml
index 900a1ca3..bacbf7a4 100644
--- a/models/sevennet/sevennet-0.yml
+++ b/models/sevennet/sevennet-0.yml
@@ -78,7 +78,10 @@ notes:
 
 metrics:
   phonons:
-    κ_SRME: 0.767
+    kappa_103:
+      κ_SRME: 0.767
+      pred_file: models/sevennet/sevennet-0/2024-11-09-kappa-103-FIRE-dist=0.01-fmax=1e-4-symprec=1e-5.json.gz
+      pred_file_url: https://figshare.com/ndownloader/files/52134878
   geo_opt:
     pred_file: models/sevennet/sevennet-0/2024-07-11-wbm-geo-opt.json.gz
     pred_file_url: https://figshare.com/ndownloader/files/52062035
diff --git a/models/sevennet/sevennet-l3i5.yml b/models/sevennet/sevennet-l3i5.yml
index 3f8db7e0..ff9b7785 100644
--- a/models/sevennet/sevennet-l3i5.yml
+++ b/models/sevennet/sevennet-l3i5.yml
@@ -77,7 +77,10 @@ notes:
 
 metrics:
   phonons:
-    κ_SRME: 0.550
+    kappa_103:
+      κ_SRME: 0.550
+      pred_file: models/sevennet/sevennet-l3i5/2024-12-10-kappa-103-FIRE-dist=0.01-fmax=1e-4-symprec=1e-5.json.gz
+      pred_file_url: https://figshare.com/ndownloader/files/52134881
   geo_opt:
     pred_file: models/sevennet/sevennet-l3i5/2024-12-10-wbm-geo-opt.json.gz
     pred_file_url: https://figshare.com/ndownloader/files/52062056
diff --git a/scripts/metrics/eval_kappa_srme.py b/scripts/metrics/eval_kappa_srme.py
index 1e09f8aa..191d617c 100644
--- a/scripts/metrics/eval_kappa_srme.py
+++ b/scripts/metrics/eval_kappa_srme.py
@@ -3,25 +3,26 @@
 """
 
 # %%
+import os
+
 import pandas as pd
 from pymatviz.enums import Key
 
 from matbench_discovery.data import DataFiles, Model
 from matbench_discovery.metrics import phonons
 
-model_name = "mace-omat-0-medium"
-in_folder = f"2025-01-28-{model_name}-phononDB-LTC-FIRE_2SR_force0.0001_sym1e-05"
-model_dir = Model.mace_mpa_0.yaml_path.rsplit("/", 1)[0]
-in_path = f"{model_dir}/{in_folder}/kappa.json.gz"
+for model in Model:
+    if model.kappa_103_path is None or not os.path.isfile(model.kappa_103_path):
+        continue
 
-df_ml = pd.read_json(in_path).set_index(Key.mat_id)
+    df_ml = pd.read_json(model.kappa_103_path).set_index(Key.mat_id)
 
-json_path = DataFiles.phonondb_pbe_103_kappa_no_nac.path
-df_dft = pd.read_json(json_path).set_index("mp_id")
+    json_path = DataFiles.phonondb_pbe_103_kappa_no_nac.path
+    df_dft = pd.read_json(json_path).set_index(Key.mat_id)
 
-df_ml_metrics = phonons.calc_kappa_metrics_from_dfs(df_ml, df_dft)
+    df_ml_metrics = phonons.calc_kappa_metrics_from_dfs(df_ml, df_dft)
 
-kappa_sre = df_ml_metrics[Key.sre].mean()
-kappa_srme = df_ml_metrics[Key.srme].mean()
+    kappa_sre = df_ml_metrics[Key.sre].mean()
+    kappa_srme = df_ml_metrics[Key.srme].mean()
 
-print(f"{model_name = }\n\t{kappa_srme = :.6f}\n\t{kappa_sre = :.6f}")
+    print(f"{model.label=}\n\t{kappa_srme=:.4f}\n\t{kappa_sre=:.4f}")
diff --git a/scripts/upload_model_preds_to_figshare.py b/scripts/upload_model_preds_to_figshare.py
index 98a91113..327edfcc 100644
--- a/scripts/upload_model_preds_to_figshare.py
+++ b/scripts/upload_model_preds_to_figshare.py
@@ -170,7 +170,7 @@ def find_file_keys(data: dict[str, Any], prefix: str = "") -> dict[str, str]:
                 if file_hash == md5_hash:
                     file_url = f"{figshare.DOWNLOAD_URL_PREFIX}/{file_id}"
                     # Update model metadata if URL not present
-                    url_key = f"{key_path[:-5]}_url"  # replace _file with _url
+                    url_key = f"{key_path}_url"  # append _url to YAML key
                     if url_key not in metric_data:
                         *parts, last = url_key.split(".")
                         target = metric_data
@@ -187,7 +187,7 @@ def find_file_keys(data: dict[str, Any], prefix: str = "") -> dict[str, str]:
                         )
                         file_url = f"{figshare.DOWNLOAD_URL_PREFIX}/{file_id}"
                         updated_files[filename] = file_url
-                        *parts, last = key_path[:-5].split(".")
+                        *parts, last = key_path.split(".")
                         target = metric_data
                         for part in parts:
                             target = target[part]
@@ -202,7 +202,7 @@ def find_file_keys(data: dict[str, Any], prefix: str = "") -> dict[str, str]:
                     )
                     file_url = f"{figshare.DOWNLOAD_URL_PREFIX}/{file_id}"
                     new_files[filename] = file_url
-                    *parts, last = key_path[:-5].split(".")
+                    *parts, last = key_path.split(".")
                     target = metric_data
                     for part in parts:
                         target = target[part]
diff --git a/site/src/figs/energy-parity/e-form-parity-mattersim-v1.svelte b/site/src/figs/energy-parity/e-form-parity-mattersim-v1-5M.svelte
similarity index 100%
rename from site/src/figs/energy-parity/e-form-parity-mattersim-v1.svelte
rename to site/src/figs/energy-parity/e-form-parity-mattersim-v1-5M.svelte
diff --git a/site/src/figs/energy-parity/each-parity-mattersim-v1.svelte b/site/src/figs/energy-parity/each-parity-mattersim-v1-5M.svelte
similarity index 100%
rename from site/src/figs/energy-parity/each-parity-mattersim-v1.svelte
rename to site/src/figs/energy-parity/each-parity-mattersim-v1-5M.svelte
diff --git a/site/src/figs/per-element-each-errors.json b/site/src/figs/per-element-each-errors.json
index c6290f27..5bdb3f0f 100644
--- a/site/src/figs/per-element-each-errors.json
+++ b/site/src/figs/per-element-each-errors.json
@@ -1 +1 @@
-{"MP Occurrences":{"H":10409.0,"He":8.0,"Li":21576.0,"Be":1186.0,"B":6363.0,"C":9069.0,"N":11419.0,"O":81887.0,"F":12067.0,"Ne":1.0,"Na":12795.0,"Mg":19007.0,"Al":7803.0,"Si":12756.0,"P":16814.0,"S":15341.0,"Cl":6385.0,"Ar":2.0,"K":8034.0,"Ca":8422.0,"Sc":2686.0,"Ti":7721.0,"V":9703.0,"Cr":6774.0,"Mn":13966.0,"Fe":12889.0,"Co":11045.0,"Ni":8293.0,"Cu":9903.0,"Zn":6905.0,"Ga":5076.0,"Ge":5497.0,"As":3894.0,"Se":6509.0,"Br":3011.0,"Kr":15.0,"Rb":4599.0,"Sr":7297.0,"Y":5012.0,"Zr":3847.0,"Nb":5460.0,"Mo":5411.0,"Tc":696.0,"Ru":2453.0,"Rh":2512.0,"Pd":2985.0,"Ag":4109.0,"Cd":3396.0,"In":4400.0,"Sn":6157.0,"Sb":5784.0,"Te":4980.0,"I":3004.0,"Xe":157.0,"Cs":4071.0,"Ba":8338.0,"La":5599.0,"Ce":3271.0,"Pr":2894.0,"Nd":3234.0,"Pm":537.0,"Sm":2902.0,"Eu":2431.0,"Gd":1659.0,"Tb":2225.0,"Dy":2318.0,"Ho":2164.0,"Er":2208.0,"Tm":1752.0,"Yb":2121.0,"Lu":1634.0,"Hf":2729.0,"Ta":3407.0,"W":5121.0,"Re":1476.0,"Os":1229.0,"Ir":2053.0,"Pt":2444.0,"Au":2515.0,"Hg":2341.0,"Tl":2998.0,"Pb":3021.0,"Bi":4936.0,"Po":null,"At":null,"Rn":null,"Fr":null,"Ra":null,"Ac":304.0,"Th":1059.0,"Pa":286.0,"U":2439.0,"Np":410.0,"Pu":463.0,"Am":null,"Cm":null,"Bk":null,"Cf":null,"Es":null,"Fm":null,"Md":null,"No":null,"Lr":null,"Rf":null,"Db":null,"Sg":null,"Bh":null,"Hs":null,"Mt":null,"Ds":null,"Rg":null,"Cn":null,"Nh":null,"Fl":null,"Mc":null,"Lv":null,"Ts":null,"Og":null},"Test 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RF":{"H":0.5852,"He":null,"Li":0.2397,"Be":0.3723,"B":0.4883,"C":0.3561,"N":0.6895,"O":0.8696,"F":0.9991,"Ne":null,"Na":0.343,"Mg":0.2674,"Al":0.3046,"Si":0.3326,"P":0.348,"S":0.4893,"Cl":0.6792,"Ar":null,"K":0.2976,"Ca":0.3204,"Sc":0.2653,"Ti":0.2909,"V":0.4008,"Cr":0.5226,"Mn":0.4134,"Fe":0.4606,"Co":0.3263,"Ni":0.2564,"Cu":0.303,"Zn":0.2979,"Ga":0.2673,"Ge":0.3121,"As":0.3353,"Se":0.4864,"Br":0.6571,"Kr":null,"Rb":0.2931,"Sr":0.3244,"Y":0.2614,"Zr":0.2812,"Nb":0.3315,"Mo":0.2963,"Tc":0.2498,"Ru":0.4354,"Rh":0.2814,"Pd":0.2694,"Ag":0.28,"Cd":0.2878,"In":0.3613,"Sn":0.287,"Sb":0.3013,"Te":0.455,"I":0.5407,"Xe":0.076,"Cs":0.2848,"Ba":0.3013,"La":0.2559,"Ce":0.265,"Pr":0.2719,"Nd":0.2613,"Pm":0.2154,"Sm":0.2634,"Eu":0.2884,"Gd":0.2453,"Tb":0.2768,"Dy":0.2806,"Ho":0.2812,"Er":0.2851,"Tm":0.2965,"Yb":0.3509,"Lu":0.2478,"Hf":0.3319,"Ta":0.4082,"W":0.3084,"Re":0.2557,"Os":0.451,"Ir":0.3447,"Pt":0.2778,"Au":0.3426,"Hg":0.2602,"Tl":0.3566,"Pb":0.3953,"Bi":0.293,"Po":null,"At":null,"Rn":null,"Fr":null,"Ra":null,"Ac":0.226,"Th":0.3121,"Pa":0.2956,"U":0.4561,"Np":0.4963,"Pu":0.3884,"Am":null,"Cm":null,"Bk":null,"Cf":null,"Es":null,"Fm":null,"Md":null,"No":null,"Lr":null,"Rf":null,"Db":null,"Sg":null,"Bh":null,"Hs":null,"Mt":null,"Ds":null,"Rg":null,"Cn":null,"Nh":null,"Fl":null,"Mc":null,"Lv":null,"Ts":null,"Og":null},"each_err_models":{"H":0.3396,"He":null,"Li":0.0928,"Be":0.1485,"B":0.2018,"C":0.1676,"N":0.2534,"O":0.3268,"F":0.3993,"Ne":null,"Na":0.114,"Mg":0.1121,"Al":0.1664,"Si":0.1854,"P":0.171,"S":0.2493,"Cl":0.3134,"Ar":null,"K":0.1262,"Ca":0.1179,"Sc":0.1209,"Ti":0.1554,"V":0.2026,"Cr":0.1855,"Mn":0.2006,"Fe":0.2095,"Co":0.1543,"Ni":0.1375,"Cu":0.1213,"Zn":0.1267,"Ga":0.1411,"Ge":0.1556,"As":0.1589,"Se":0.2416,"Br":0.2743,"Kr":null,"Rb":0.1258,"Sr":0.1147,"Y":0.1215,"Zr":0.1448,"Nb":0.1778,"Mo":0.1514,"Tc":0.1095,"Ru":0.1734,"Rh":0.1473,"Pd":0.1366,"Ag":0.1074,"Cd":0.1054,"In":0.1482,"Sn":0.1437,"Sb":0.1394,"Te":0.2282,"I":0.2263,"Xe":0.2794,"Cs":0.128,"Ba":0.1182,"La":0.1144,"Ce":0.1146,"Pr":0.1094,"Nd":0.1075,"Pm":0.0874,"Sm":0.1098,"Eu":0.1188,"Gd":0.1154,"Tb":0.1132,"Dy":0.1164,"Ho":0.1138,"Er":0.1144,"Tm":0.1174,"Yb":0.1198,"Lu":0.1119,"Hf":0.1502,"Ta":0.2229,"W":0.1357,"Re":0.135,"Os":0.1672,"Ir":0.1751,"Pt":0.1544,"Au":0.1473,"Hg":0.0954,"Tl":0.1152,"Pb":0.1428,"Bi":0.1221,"Po":null,"At":null,"Rn":null,"Fr":null,"Ra":null,"Ac":0.0848,"Th":0.1689,"Pa":0.1404,"U":0.1636,"Np":0.2404,"Pu":0.332,"Am":null,"Cm":null,"Bk":null,"Cf":null,"Es":null,"Fm":null,"Md":null,"No":null,"Lr":null,"Rf":null,"Db":null,"Sg":null,"Bh":null,"Hs":null,"Mt":null,"Ds":null,"Rg":null,"Cn":null,"Nh":null,"Fl":null,"Mc":null,"Lv":null,"Ts":null,"Og":null}}
diff --git a/site/src/lib/MetricsTable.svelte b/site/src/lib/MetricsTable.svelte
index 53b878ac..ef85e7cb 100644
--- a/site/src/lib/MetricsTable.svelte
+++ b/site/src/lib/MetricsTable.svelte
@@ -131,7 +131,7 @@
         MAE: metrics?.MAE,
         RMSE: metrics?.RMSE,
         'R<sup>2</sup>': metrics?.R2,
-        'κ<sub>SRME</sub>': model.metrics?.phonons?.κ_SRME,
+        'κ<sub>SRME</sub>': model.metrics?.phonons?.kappa_103?.κ_SRME,
         'Training Set': format_train_set(model.training_set),
         Params: `<span title="${pretty_num(model.model_params, `,`)} trainable model parameters">${pretty_num(model.model_params)}</span>`,
         Targets: targets_str,
diff --git a/site/src/lib/ModelCard.svelte b/site/src/lib/ModelCard.svelte
index 1cd56633..9ecfc184 100644
--- a/site/src/lib/ModelCard.svelte
+++ b/site/src/lib/ModelCard.svelte
@@ -19,7 +19,9 @@
   $: ({ model_params, hyperparams, notes = {}, training_set, n_estimators } = model)
   $: all_metrics = {
     ...(model.metrics?.discovery?.full_test_set ?? {}),
-    ...(typeof model.metrics?.phonons == `object` ? model.metrics?.phonons : {}),
+    ...(typeof model.metrics?.phonons == `object`
+      ? model.metrics?.phonons.kappa_103
+      : {}),
   }
 
   $: ({ missing_preds, missing_percent } = all_metrics)
diff --git a/site/src/lib/model-schema.d.ts b/site/src/lib/model-schema.d.ts
index 3fb9eb7e..948c5926 100644
--- a/site/src/lib/model-schema.d.ts
+++ b/site/src/lib/model-schema.d.ts
@@ -83,113 +83,18 @@ export interface ModelMetadata {
   metrics?: {
     phonons?:
       | {
-          pred_file?: string | null
-          pred_file_url?: string | null
-          κ_SRME?: number
+          kappa_103?: {
+            [k: string]: unknown
+          }
         }
       | ('not applicable' | 'not available')
     geo_opt?:
       | {
-          pred_file: string | null
-          pred_file_url: string | null
-          pred_col: string | null
-          'symprec=1e-5'?: {
-            rmsd?: number
-            n_sym_ops_mae?: number
-            symmetry_decrease?: number
-            symmetry_match?: number
-            symmetry_increase?: number
-            n_structures?: number
-            analysis_file: string
-            analysis_file_url?: string
-          }
-          'symprec=1e-3'?: {
-            rmsd?: number
-            n_sym_ops_mae?: number
-            symmetry_decrease?: number
-            symmetry_match?: number
-            symmetry_increase?: number
-            n_structures?: number
-            analysis_file: string
-            analysis_file_url?: string
-          }
-          'symprec=1e-2'?: {
-            rmsd?: number
-            n_sym_ops_mae?: number
-            symmetry_decrease?: number
-            symmetry_match?: number
-            symmetry_increase?: number
-            n_structures?: number
-            analysis_file: string
-            analysis_file_url?: string
-          }
+          [k: string]: unknown
         }
       | ('not applicable' | 'not available')
     discovery?: {
-      additionalProperties?: never
-      pred_file: string
-      pred_file_url: string
-      pred_col: string
-      full_test_set?: {
-        F1?: number
-        DAF?: number
-        Precision?: number
-        Recall?: number
-        Accuracy?: number
-        TPR?: number
-        FPR?: number
-        TNR?: number
-        FNR?: number
-        TP?: number
-        FP?: number
-        TN?: number
-        FN?: number
-        MAE?: number
-        RMSE?: number
-        R2?: number
-        missing_preds?: number
-        missing_percent?: string
-      }
-      most_stable_10k?: {
-        F1?: number
-        DAF?: number
-        Precision?: number
-        Recall?: number
-        Accuracy?: number
-        TPR?: number
-        FPR?: number
-        TNR?: number
-        FNR?: number
-        TP?: number
-        FP?: number
-        TN?: number
-        FN?: number
-        MAE?: number
-        RMSE?: number
-        R2?: number
-        missing_preds?: number
-        missing_percent?: string
-      }
-      unique_prototypes?: {
-        F1?: number
-        DAF?: number
-        Precision?: number
-        Recall?: number
-        Accuracy?: number
-        TPR?: number
-        FPR?: number
-        TNR?: number
-        FNR?: number
-        TP?: number
-        FP?: number
-        TN?: number
-        FN?: number
-        MAE?: number
-        RMSE?: number
-        R2?: number
-        missing_preds?: number
-        missing_percent?: string
-      }
+      [k: string]: unknown
     }
   }
 }
diff --git a/site/src/routes/tasks/geo-opt/geo-opt-readme.md b/site/src/routes/tasks/geo-opt/geo-opt-readme.md
index dbd0d349..59b0ad3d 100644
--- a/site/src/routes/tasks/geo-opt/geo-opt-readme.md
+++ b/site/src/routes/tasks/geo-opt/geo-opt-readme.md
@@ -1,6 +1,6 @@
 # MLFF Geometry Optimization Analysis
 
-> Disclaimer: There is a caveat to the structure similarity analysis below. The WBM test set was generated using the `MPRelaxSet` which applies [`ISYM=2`](https://vasp.at/wiki/index.php/ISIF). This fixes the structure's symmetry. The MLFFs by contrast use the FIRE or LBFGS optimizers with no symmetry constraints. They may therefore in some cases relax to lower energy states with different symmetry. This is not a mistake of the model and so higher σ<sub>match</sub> (the percentage of structures with matching ML and DFT spacegroups) is not necessarily indicative of a better model. Thanks to [Alex Ganose](https://scholar.google.co.uk/citations?user=nVJFXWwAAAAJ) for pointing this out! Undiscovered lower energy structures in the relatively well-explored chemical systems covered by WBM and MP are not expected to be a common occurrence. Hence we believe this analysis still provides some useful insight.
+> Disclaimer: There is a caveat to the structure similarity analysis below. The WBM test set was generated using the `MPRelaxSet` which applies [`ISYM=2`](https://vasp.at/wiki/index.php/ISIF). This fixes the structure's symmetry. The MLFFs by contrast use the FIRE or LBFGS optimizers with no symmetry constraints. They may therefore in some cases relax to lower energy states with different symmetry. This is not a mistake of the model and so higher σ<sub>match</sub> (the percentage of structures with matching ML and DFT spacegroups) is not necessarily indicative of a better model. Thanks to [Alex Ganose](https://scholar.google.co.uk/citations?user=nVJFXWwAAAAJ) for pointing this out! Undiscovered lower energy and lower symmetry structures in the well-explored chemical systems covered by WBM and MP are not expected to be a common occurrence. Hence we believe this analysis still provides some useful insight.
 
 All plots/metrics below evaluate the quality of MLFF relaxations for the 257k crystal structures in the [WBM test set](https://nature.com/articles/s41524-020-00481-6). Not all models were able to relax all structures (user/cluster error may explain some failures) but every model was evaluated on at least <slot name="min-relaxed-structures"/> relaxations.
 
diff --git a/site/tests/model-card.test.ts b/site/tests/model-card.test.ts
index a17f2e84..0a65f83a 100644
--- a/site/tests/model-card.test.ts
+++ b/site/tests/model-card.test.ts
@@ -108,7 +108,7 @@ describe(`ModelCard`, () => {
       expect(f1_metric?.classList.contains(`active`)).toBe(true)
 
       const kappa_metric = Array.from(metrics).find((m) => m.textContent?.includes(`κ`))
-      const kappa_value = model.metrics?.phonons?.κ_SRME
+      const kappa_value = model.metrics?.phonons?.kappa_103?.κ_SRME
       expect(kappa_metric?.querySelector(`strong`)?.textContent?.trim()).toBe(
         `${kappa_value} W/mK`,
       )
diff --git a/tests/model-schema.yml b/tests/model-schema.yml
index 228c19f2..50d4c664 100644
--- a/tests/model-schema.yml
+++ b/tests/model-schema.yml
@@ -146,30 +146,51 @@ properties:
           - type: object
             additionalProperties: false
             properties:
-              pred_file:
-                type: [string, "null"]
-              pred_file_url:
-                type: [string, "null"]
-              κ_SRME:
-                type: number
+              kappa_103:
+                type: object
+                additionalProperties: false
+                required: ["κ_SRME"]
+                properties:
+                  κ_SRME:
+                    type: number
+                    description: Symmetric Relative Mean Error for thermal conductivity predictions
+                  pred_file:
+                    type: [string, "null"]
+                    description: Path to the predictions file containing thermal conductivity results
+                  pred_file_url:
+                    type: [string, "null"]
+                    format: uri
+                    pattern: "^https?://"
+                    description: URL to download the predictions file
+                allOf:
+                  - if:
+                      properties:
+                        pred_file: { type: string }
+                      required: [pred_file]
+                    then:
+                      required: [pred_file_url]
+                      properties:
+                        pred_file_url:
+                          { type: string, format: uri, pattern: "^https?://" }
           - type: string
             enum: [not applicable, not available]
       geo_opt:
         oneOf:
           - type: object
             additionalProperties: false
-            required: [pred_file, pred_col, pred_file_url]
+            required: [pred_col]
             properties:
               pred_file:
                 type: [string, "null"]
               pred_file_url:
                 type: [string, "null"]
+                format: uri
+                pattern: "^https?://"
               pred_col:
-                type: [string, "null"]
+                type: string
               symprec=1e-5: &symprec_metrics
                 type: object
                 additionalProperties: false
-                required: [analysis_file]
                 properties:
                   rmsd:
                     type: number
@@ -184,23 +205,46 @@ properties:
                   n_structures:
                     type: number
                   analysis_file:
-                    type: string
+                    type: [string, "null"]
                   analysis_file_url:
-                    type: string
+                    type: [string, "null"]
+                    format: uri
+                    pattern: "^https?://"
+                allOf:
+                  - if:
+                      properties:
+                        analysis_file: { type: string }
+                      required: [analysis_file]
+                    then:
+                      required: [analysis_file_url]
+                      properties:
+                        analysis_file_url:
+                          { type: string, format: uri, pattern: "^https?://" }
               symprec=1e-3: *symprec_metrics
               symprec=1e-2: *symprec_metrics
+            allOf:
+              - if:
+                  properties:
+                    pred_file: { type: string }
+                  required: [pred_file]
+                then:
+                  required: [pred_file_url]
+                  properties:
+                    pred_file_url:
+                      { type: string, format: uri, pattern: "^https?://" }
           - type: string
             enum: [not applicable, not available]
       discovery:
         additionalProperties: false
-        required: [pred_file, pred_col, pred_file_url]
+        required: [pred_col]
         type: object
         properties:
-          additionalProperties: false
           pred_file:
-            type: string
+            type: [string, "null"]
           pred_file_url:
-            type: string
+            type: [string, "null"]
+            format: uri
+            pattern: "^https?://"
           pred_col:
             type: string
           full_test_set: &discovery_metrics
@@ -245,6 +289,16 @@ properties:
                 type: string
           most_stable_10k: *discovery_metrics
           unique_prototypes: *discovery_metrics
+        allOf:
+          - if:
+              properties:
+                pred_file: { type: string }
+              required: [pred_file]
+            then:
+              required: [pred_file_url]
+              properties:
+                pred_file_url:
+                  { type: string, format: uri, pattern: "^https?://" }
 
 required:
   - authors
diff --git a/tests/phonons/test_thermal_conductivity.py b/tests/phonons/test_thermal_conductivity.py
index fd3691fd..b7e53071 100644
--- a/tests/phonons/test_thermal_conductivity.py
+++ b/tests/phonons/test_thermal_conductivity.py
@@ -15,6 +15,7 @@
 from matbench_discovery.phonons.thermal_conductivity import calculate_fc2_set
 
 NP_RNG = np.random.default_rng(seed=0)
+init_keys = ("fc2_supercell", "fc3_supercell", "q_point_mesh")
 
 
 @pytest.fixture
@@ -23,14 +24,15 @@ def test_atoms() -> Atoms:
     atoms = bulk("Al", "fcc", a=4.05)
     atoms.info["fc2_supercell"] = 2 * np.eye(3)
     atoms.info["fc3_supercell"] = np.eye(3)
-    atoms.info["q_mesh"] = [2, 2, 2]
+    atoms.info["q_point_mesh"] = [2, 2, 2]
     return atoms
 
 
 @pytest.fixture
 def test_ph3(test_atoms: Atoms) -> Phono3py:
     """Create a test Phono3py object."""
-    return ltc.init_phono3py(test_atoms)
+    keys = ("fc2_supercell", "fc3_supercell", "q_point_mesh")
+    return ltc.init_phono3py(test_atoms, **{key: test_atoms.info[key] for key in keys})
 
 
 @pytest.fixture
@@ -41,17 +43,54 @@ def test_calculator() -> EMT:
 
 def test_init_phono3py(test_atoms: Atoms) -> None:
     """Test initialization of Phono3py object."""
-    ph3 = ltc.init_phono3py(test_atoms)
+    fc2_supercell = test_atoms.info["fc2_supercell"]
+    fc3_supercell = test_atoms.info["fc3_supercell"]
+    q_point_mesh = test_atoms.info["q_point_mesh"]
+    ph3 = ltc.init_phono3py(
+        test_atoms,
+        fc2_supercell=fc2_supercell,
+        fc3_supercell=fc3_supercell,
+        q_point_mesh=q_point_mesh,
+    )
     assert isinstance(ph3, Phono3py)
     assert list(ph3.mesh_numbers) == [2, 2, 2]
     assert ph3.supercell_matrix.tolist() == np.eye(3).tolist()
-
-
-def test_init_phono3py_missing_info(test_atoms: Atoms) -> None:
-    """Test initialization with missing metadata."""
-    test_atoms.info.pop("fc2_supercell")
-    with pytest.raises(ValueError, match="fc2_supercell.*not found"):
-        ltc.init_phono3py(test_atoms)
+    # Check that both supercells were created correctly
+    assert np.allclose(ph3.phonon_supercell_matrix, fc2_supercell)
+    assert np.allclose(ph3.supercell_matrix, fc3_supercell)
+    # Verify supercell sizes
+    assert len(ph3.phonon_supercell) == len(test_atoms) * 8  # 2x2x2 supercell
+    assert len(ph3.supercell) == len(test_atoms)  # 1x1x1 supercell
+
+
+def test_init_phono3py_custom_mesh_and_displacement(test_atoms: Atoms) -> None:
+    """Test initialization with custom mesh and displacement distance."""
+    # Test custom mesh
+    custom_mesh = (4, 4, 4)
+    ph3 = ltc.init_phono3py(
+        test_atoms,
+        fc2_supercell=test_atoms.info["fc2_supercell"],
+        fc3_supercell=test_atoms.info["fc3_supercell"],
+        q_point_mesh=custom_mesh,
+    )
+    assert tuple(ph3.mesh_numbers) == custom_mesh
+    # Phono3py automatically initializes mesh when setting mesh_numbers
+    assert len(ph3.grid.addresses) == 89
+
+    custom_displacement = 0.05
+    ph3 = ltc.init_phono3py(
+        test_atoms,
+        fc2_supercell=test_atoms.info["fc2_supercell"],
+        fc3_supercell=test_atoms.info["fc3_supercell"],
+        q_point_mesh=test_atoms.info["q_point_mesh"],
+        displacement_distance=custom_displacement,
+    )
+    # Check that displacements were generated with the custom distance
+    displacements = ph3.displacements
+    # Phono3py generates displacements of exactly the specified magnitude
+    disp_magnitudes = np.linalg.norm(displacements, axis=-1)
+    non_zero_disps = disp_magnitudes[disp_magnitudes > 0]
+    np.testing.assert_allclose(non_zero_disps, custom_displacement)
 
 
 def test_calculate_fc2_set(test_ph3: Phono3py, test_calculator: EMT) -> None:
@@ -242,7 +281,7 @@ def test_calculate_fc2_set_null_supercell() -> None:
     calc = MockCalculator(np.zeros((2, 3)))
     force_set = calculate_fc2_set(ph3, calc, pbar_kwargs={"disable": True})
 
-    # Test that ones are used for null supercell case
+    # Test that zeros are used for null supercell case
     np.testing.assert_allclose(force_set, np.zeros((2, len(ph3.phonon_supercell), 3)))
 
     # Verify shape is correct even with null supercell
diff --git a/tests/test_data.py b/tests/test_data.py
index 6656aa0e..efe84c27 100644
--- a/tests/test_data.py
+++ b/tests/test_data.py
@@ -243,6 +243,9 @@ def test_model() -> None:
 
     # Test yaml_path property
     assert Model.alignn.yaml_path.endswith("alignn/alignn.yml")
+    assert Model.grace2l_r6.kappa_103_path.endswith(
+        "2024-11-20-kappa-103-FIRE-fmax=1e-4-symprec=1e-5.json.gz"
+    )
 
     # Test error handling for missing paths
     with pytest.raises(
diff --git a/tests/test_models.py b/tests/test_models.py
index 5d6a2a0a..4261b31d 100644
--- a/tests/test_models.py
+++ b/tests/test_models.py
@@ -128,7 +128,7 @@ def test_model_enum() -> None:
         (Model.wrenformer, True),
         (Model.voronoi_rf, True),
         (Model.gnome, False),
-        (Model.mattersim, False),
+        (Model.mattersim_v1_5m, False),
     ],
 )
 def test_model_is_compliant(model_key: Model, is_compliant: bool) -> None: