Datasets:

arifmohamedkhan
/

Certify

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
n_mol: int64
r2_mean: double
r2_std: double
mae_mean: double
dataset_type: string
metric_schnet_gap_f1: struct<keys: list<item: string>, size_bytes: int64>
  child 0, keys: list<item: string>
      child 0, item: string
  child 1, size_bytes: int64
metric_schnet_homo_f0: struct<keys: list<item: string>, size_bytes: int64>
  child 0, keys: list<item: string>
      child 0, item: string
  child 1, size_bytes: int64
metric_schnet_cv_f1: struct<keys: list<item: string>, size_bytes: int64>
  child 0, keys: list<item: string>
      child 0, item: string
  child 1, size_bytes: int64
metric_schnet_mu_f4: struct<keys: list<item: string>, size_bytes: int64>
  child 0, keys: list<item: string>
      child 0, item: string
  child 1, size_bytes: int64
metric_schnet_mu_f0: struct<keys: list<item: string>, size_bytes: int64>
  child 0, keys: list<item: string>
      child 0, item: string
  child 1, size_bytes: int64
metric_schnet_lumo_f0: struct<keys: list<item: string>, size_bytes: int64>
  child 0, keys: list<item: string>
      child 0, item: string
  child 1, size_bytes: int64
n_figures: int64
metric_schnet_cv_f4: struct<keys: list<item: string>, size_bytes: int64>
  child 0, keys: list<item: string>
      child 0, item: string
  child 1, size_bytes: int64
n_fold_files: int64
metric_method_theory_boost: struct<keys: list<item: string>, size_bytes: int64>
  child 0, keys: list<item: string>
      child 0, item: string
  child 1, size_bytes: int64
metric_schnet_mu_f2: struct<keys: list<it
...
_bytes: int64>
  child 0, keys: list<item: string>
      child 0, item: string
  child 1, size_bytes: int64
n_metrics: int64
metric_schnet_lumo_f3: struct<keys: list<item: string>, size_bytes: int64>
  child 0, keys: list<item: string>
      child 0, item: string
  child 1, size_bytes: int64
metric_qm7b_full: struct<keys: list<item: string>, size_bytes: int64>
  child 0, keys: list<item: string>
      child 0, item: string
  child 1, size_bytes: int64
generated: string
n_checkpoints: int64
metric_schnet_homo_f3: struct<keys: list<item: string>, size_bytes: int64>
  child 0, keys: list<item: string>
      child 0, item: string
  child 1, size_bytes: int64
metric_schnet_homo_f2: struct<keys: list<item: string>, size_bytes: int64>
  child 0, keys: list<item: string>
      child 0, item: string
  child 1, size_bytes: int64
metric_holm_bonferroni: struct<keys: list<item: string>, size_bytes: int64>
  child 0, keys: list<item: string>
      child 0, item: string
  child 1, size_bytes: int64
metric_schnet_homo_f1: struct<keys: list<item: string>, size_bytes: int64>
  child 0, keys: list<item: string>
      child 0, item: string
  child 1, size_bytes: int64
metric_failure_cases: struct<keys: list<item: string>, size_bytes: int64>
  child 0, keys: list<item: string>
      child 0, item: string
  child 1, size_bytes: int64
metric_schnet_cv_f2: struct<keys: list<item: string>, size_bytes: int64>
  child 0, keys: list<item: string>
      child 0, item: string
  child 1, size_bytes: int64
to
{'generated': Value('string'), 'n_backup_dirs': Value('int64'), 'backup_dirs': List(Value('string')), 'n_figures': Value('int64'), 'n_metrics': Value('int64'), 'n_checkpoints': Value('int64'), 'n_fold_files': Value('int64'), 'n_scripts': Value('int64'), 'metric_failure_cases': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_lumo_f2': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_data_speaks': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_phase2_results': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_lumo_f3': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_mu_f0': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_cv_f1': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_timing_benchmarks': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_reproducibility_report': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_homo_f2': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_results': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_mu_f2': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_mu_f1': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_homo_f4': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_holm_bonferron
...
int64')}, 'metric_schnet_gap_f3': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_method_theory_boost': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_lumo_f4': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_cv_f2': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_ESOL_results': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_FreeSolv_results': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_mu_f3': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_mu_f4': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_cv_f0': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_homo_f1': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_software_versions': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_cross_rep_tests': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_cv_f4': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_lumo_f1': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_gap_f1': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_lumo_f0': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_cv_f3': {'keys': List(Value('string')), 'size_bytes': Value('int64')}}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 129, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 544, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 3052, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2559, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 558, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 361, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2381, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              n_mol: int64
              r2_mean: double
              r2_std: double
              mae_mean: double
              dataset_type: string
              metric_schnet_gap_f1: struct<keys: list<item: string>, size_bytes: int64>
                child 0, keys: list<item: string>
                    child 0, item: string
                child 1, size_bytes: int64
              metric_schnet_homo_f0: struct<keys: list<item: string>, size_bytes: int64>
                child 0, keys: list<item: string>
                    child 0, item: string
                child 1, size_bytes: int64
              metric_schnet_cv_f1: struct<keys: list<item: string>, size_bytes: int64>
                child 0, keys: list<item: string>
                    child 0, item: string
                child 1, size_bytes: int64
              metric_schnet_mu_f4: struct<keys: list<item: string>, size_bytes: int64>
                child 0, keys: list<item: string>
                    child 0, item: string
                child 1, size_bytes: int64
              metric_schnet_mu_f0: struct<keys: list<item: string>, size_bytes: int64>
                child 0, keys: list<item: string>
                    child 0, item: string
                child 1, size_bytes: int64
              metric_schnet_lumo_f0: struct<keys: list<item: string>, size_bytes: int64>
                child 0, keys: list<item: string>
                    child 0, item: string
                child 1, size_bytes: int64
              n_figures: int64
              metric_schnet_cv_f4: struct<keys: list<item: string>, size_bytes: int64>
                child 0, keys: list<item: string>
                    child 0, item: string
                child 1, size_bytes: int64
              n_fold_files: int64
              metric_method_theory_boost: struct<keys: list<item: string>, size_bytes: int64>
                child 0, keys: list<item: string>
                    child 0, item: string
                child 1, size_bytes: int64
              metric_schnet_mu_f2: struct<keys: list<it
              ...
              _bytes: int64>
                child 0, keys: list<item: string>
                    child 0, item: string
                child 1, size_bytes: int64
              n_metrics: int64
              metric_schnet_lumo_f3: struct<keys: list<item: string>, size_bytes: int64>
                child 0, keys: list<item: string>
                    child 0, item: string
                child 1, size_bytes: int64
              metric_qm7b_full: struct<keys: list<item: string>, size_bytes: int64>
                child 0, keys: list<item: string>
                    child 0, item: string
                child 1, size_bytes: int64
              generated: string
              n_checkpoints: int64
              metric_schnet_homo_f3: struct<keys: list<item: string>, size_bytes: int64>
                child 0, keys: list<item: string>
                    child 0, item: string
                child 1, size_bytes: int64
              metric_schnet_homo_f2: struct<keys: list<item: string>, size_bytes: int64>
                child 0, keys: list<item: string>
                    child 0, item: string
                child 1, size_bytes: int64
              metric_holm_bonferroni: struct<keys: list<item: string>, size_bytes: int64>
                child 0, keys: list<item: string>
                    child 0, item: string
                child 1, size_bytes: int64
              metric_schnet_homo_f1: struct<keys: list<item: string>, size_bytes: int64>
                child 0, keys: list<item: string>
                    child 0, item: string
                child 1, size_bytes: int64
              metric_failure_cases: struct<keys: list<item: string>, size_bytes: int64>
                child 0, keys: list<item: string>
                    child 0, item: string
                child 1, size_bytes: int64
              metric_schnet_cv_f2: struct<keys: list<item: string>, size_bytes: int64>
                child 0, keys: list<item: string>
                    child 0, item: string
                child 1, size_bytes: int64
              to
              {'generated': Value('string'), 'n_backup_dirs': Value('int64'), 'backup_dirs': List(Value('string')), 'n_figures': Value('int64'), 'n_metrics': Value('int64'), 'n_checkpoints': Value('int64'), 'n_fold_files': Value('int64'), 'n_scripts': Value('int64'), 'metric_failure_cases': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_lumo_f2': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_data_speaks': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_phase2_results': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_lumo_f3': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_mu_f0': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_cv_f1': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_timing_benchmarks': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_reproducibility_report': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_homo_f2': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_results': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_mu_f2': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_mu_f1': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_homo_f4': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_holm_bonferron
              ...
              int64')}, 'metric_schnet_gap_f3': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_method_theory_boost': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_lumo_f4': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_cv_f2': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_ESOL_results': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_FreeSolv_results': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_mu_f3': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_mu_f4': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_cv_f0': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_homo_f1': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_software_versions': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_cross_rep_tests': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_cv_f4': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_lumo_f1': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_gap_f1': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_lumo_f0': {'keys': List(Value('string')), 'size_bytes': Value('int64')}, 'metric_schnet_cv_f3': {'keys': List(Value('string')), 'size_bytes': Value('int64')}}
              because column names don't match

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You Need Geometry to Know Where Geometry Helps

Complete experimental results + code for the paper:

"Uncertainty Source Quality Determines Representation Selection for Molecular Property Prediction"

Key Finding

Topology-only (SMILES) uncertainty is universally blind to which molecules need 3D geometry. Geometry-aware (Coulomb) uncertainty can identify enrichment targets — but only for multi-body quantum properties.

You need geometry to know where geometry helps.

Three Novel Findings

Uncertainty source quality determines enrichment success — SMILES guided=random (7/7 tests), Coulomb guided≠random (4/5 tests, p<0.003)
Topology and geometry encode different physics — one-body features predict heat capacity, two-body features predict HOMO energy
Topology generalizes, geometry doesn't — scaffold split: SMILES drops R² by 0.02, Coulomb drops by 0.21

Repository Structure

├── results/
│   ├── figures/          # All generated plots (PNG + PDF)
│   ├── metrics/          # JSON files with computed results
│   └── checkpoints/      # Per-experiment DONE files + fold data
├── scripts/              # 6 Python scripts (run in order on Colab T4)
├── docs/                 # Experiment catalog + reproduction guide
└── logs/                 # Merge summary + experiment timeline

Datasets Used (all real-world, public)

QM9: 133,885 molecules, 5 quantum properties (Ramakrishnan et al. 2014)
QM7b: 7,211 molecules, 14 quantum properties (Blum & Reymond 2009)
ESOL: 1,128 molecules, aqueous solubility (Delaney 2004)
FreeSolv: 642 molecules, hydration free energy (Mobley 2014)

Statistical Rigor

5-fold CV, 5 random seeds, bootstrap 95% CI
Holm-Bonferroni correction: 15/15 tests survive
Power = 1.0 on all paired t-tests
Conformal prediction: all 15 cells within ±0.5% of target

How to Reproduce

See docs/REPRODUCIBILITY.md. Total compute: ~16 hours on a single T4 GPU (Google Colab Pro).

Citation

@article{TBD2026geometry,
  title={You Need Geometry to Know Where Geometry Helps},
  author={TBD},
  journal={Digital Discovery},
  year={2026}
}

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Total file size:

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