VERIFY — UltraMS MSnLib formula-level split (split A)
This document records what was checked, how, and with which exact values for the
msnlib_split_a_v1 tables. The split is a frozen benchmark definition: every spectrum of a
molecular formula lies in exactly one fold. All numbers below were re-derived from the
source MSnLib.csv and the shipped tables; nothing was written on the remote side.
1. Environments
| side | runtime |
|---|---|
| isolated data-preparation environment (read-only access) | Linux, Python 3.10.12, RDKit 2026.03.5, NumPy 2.2.6 |
| local post-processing (gzip twins, auxiliary voting table, cross-checks) | macOS, Python 3.13.11, NumPy 2.4.4, pandas 3.0.3, RDKit 2026.03.3 |
The molecular formula and the frozen fold assignment do not depend on the RDKit patch release. The canonical isomeric SMILES strings were frozen with RDKit 2026.03.5; other patch releases can serialise the same molecule differently (see §7).
2. Inputs
| input | identity |
|---|---|
MSnLib.csv |
560,084 data rows, 560,085 physical lines (no embedded newlines), 752,707,651 bytes, SHA-256 be54b33039cf18675751ea3c6354b592177c899a0cd5df303ae616330133ec07, columns mzs,intensities,smiles,precursor_mz,adduct,collision_energy,fold |
| MSnLib original release | 18 per-file MS2 JSONL releases; 560,084 records in total (equal to the CSV data-row count); CC BY 4.0, Zenodo record 10.5281/zenodo.11163380 |
| historical per-fold CSV files (cross-check only) | MSnLib_test.csv (57,437 rows) and MSnLib_val.csv (55,980 rows) in the same data workspace |
MSnLib_with_rt.csv (retention-time source) |
755,984,910 bytes, SHA-256 a5b7c38228287c5c1de401050445319b331ee9a5f17993d6e104e9a734fe2964; columns mzs,intensities,smiles,precursor_mz,adduct,collision_energy,fold,rt |
Access to the data workspace was read-only: MSnLib.csv and the original JSON records
were streamed out, the tables were computed in memory, and nothing was written or modified
on the remote side.
3. Definition replayed
- For every data row, parse
smileswithChem.MolFromSmilesand compute the neutral molecular formula withrdMolDescriptors.CalcMolFormula. - Read the frozen
foldlabel of the row. - Require that the fold is a function of the formula only: every formula occurs in exactly one fold.
- Export the tables.
row_formula_fold.csvis the authoritative row → formula → fold mapping for all 560,084 spectra.
4. Counts — expected versus observed (all match)
| quantity | expected | observed | status |
|---|---|---|---|
| data rows | 560,084 | 560,084 | PASS |
| unique molecular formulas | 21,107 | 21,107 | PASS |
| formulas train / validation / test | 16,885 / 2,110 / 2,112 | 16,885 / 2,110 / 2,112 | PASS |
| spectra train / validation / test | 446,667 / 55,980 / 57,437 | 446,667 / 55,980 / 57,437 | PASS |
| formulas occurring in more than one fold | 0 | 0 | PASS |
| RDKit SMILES parse failures | 0 | 0 | PASS |
| test spectra | 57,437 | 57,437 | PASS |
| validation spectra | 55,980 | 55,980 | PASS |
| voting groups, official (MSnLib source SMILES) | 5,002 | 5,002 | PASS |
| voting spectra, official (MSnLib source SMILES) | 57,436 | 57,436 | PASS |
| voting groups, canonical view | 4,888 | 4,888 | PASS |
| voting spectra, canonical view | 57,436 | 57,436 | PASS |
The formula-level proportions are 16,885 / 2,110 / 2,112 formulas (80.00 % / 10.00 % / 10.01 %) and 446,667 / 55,980 / 57,437 spectra (79.75 % / 9.99 % / 10.25 %).
Additional structure:
| quantity | value |
|---|---|
| unique source SMILES strings (all adducts) | 48,597 |
| unique canonical isomeric SMILES (all adducts) | 47,662 |
| canonical molecules with more than one source SMILES variant | 935 |
| spectra per formula: min / median / mean / max | 1 / 15 / 26.535 / 627 |
| formulas with exactly one spectrum | 25 |
| test formulas | 2,112 |
| test unique source SMILES / canonical molecules | 5,003 / 4,889 |
| validation unique source SMILES / canonical molecules | 4,883 / 4,786 |
| adducts present in the test / validation folds | 11 / 11 |
Test-fold adduct distribution: [M+H]+ 31,763, [M-H]- 13,824, [M+FA]- 5,884,
[M+Cl]- 2,403, [M+H-H2O]+ 1,252, [M+NH4]+ 1,189, [M+Na]+ 583, [M]+ 287,
[M+H-2H2O]+ 169, [M-H2O]+ 59, [M]- 24. Collision energies: 15 (4,264), 20 (30,383),
30 (6,041), 45 (3,289), 60 (13,429) and 75 eV (31).
5. Cross-checks against independent sources
5.1 Historical per-fold CSV files
The exported test and validation spectra tables were compared row by row (same order) with
MSnLib_test.csv and MSnLib_val.csv on smiles, precursor_mz, adduct and
collision_energy:
| file | rows | mismatches | status |
|---|---|---|---|
MSnLib_test.csv |
57,437 | 0 | PASS |
MSnLib_val.csv |
55,980 | 0 | PASS |
5.2 formula field of the MSnLib original JSON records
The MSnLib original release records carry an independent formula field. For every one of
the 18 original files, the RDKit formula of the first record equals the recorded
formula (18/18). Two complete files were streamed and compared record by record:
| file | records | RDKit formula ≠ recorded formula |
|---|---|---|
20241003_enammol_neg_ms2.json |
12,825 | 0 |
20241003_enammol_pos_ms2.json |
24,352 | 0 |
For the sample formula C10H10BrN5O2, three original records were located and checked;
the recorded formula equals the RDKit formula of the recorded SMILES in all three. Two of
them are different molecules that share the formula, which is exactly what the formula-level
split groups together:
| file | line | smiles | adduct |
|---|---|---|---|
20241003_mcescaf_pos_ms2.json |
9,998 | O=C1CNC(=O)N1C1CN(c2ncc(Br)cn2)C1 |
[M+H]+ |
20250828_mcediv_50k_sub_neg_ms2.json |
23,736 | O=C1CNC(=O)N1C1CN(c2ncc(Br)cn2)C1 |
[M-H]- |
20250828_mcediv_50k_sub_pos_ms2.json |
2,551 | COc1ccc(Br)cc1C(=O)Nc1nnn(C)n1 |
[M+H]+ |
MSnLib.csv contains 23 spectra with formula C10H10BrN5O2, all in the train fold
(so the sample formula does not leak into test).
5.3 Multiple-spectrum voting table of the UltraMS repository
The repository summary
benchmarks/molecular_identification/data/multiple_spectrum_voting_summary.csv reports
n_molecules = 5002 for the multiple-spectrum voting task. The per-group table
multiple_spectrum_voting_per_group.csv.gz (5,002 groups, 57,436 spectra) was compared
with our groupings:
| comparison | result |
|---|---|
repository groups vs. the official grouping by MSnLib source SMILES string (test_molecules_voting.csv) |
identical member sets and group sizes (5,002 groups, 57,436 spectra) |
| repository group strings vs. test-fold source SMILES set | all 5,002 repository strings are source SMILES strings of the test fold |
| repository groups vs. grouping by RDKit canonical isomeric SMILES | not identical: the canonical grouping merges 114 of the repository groups into 4,888 chemically identical molecules |
This is the only definition difference found; it is documented in §7 and in
REPORT.json → anomalies.
5.4 Retention-time export
msnlib_rt.csv.gz was exported from MSnLib_with_rt.csv in the data-preparation
environment. Two files were read in parallel and compared row by row:
| check | result |
|---|---|
| headers | 7-column MSnLib.csv header vs 8-column with-RT header, prefix identical |
| rows compared | 560,084 / 560,084 |
| first seven columns identical at every row | 0 mismatches |
| extra rows at the end of either file | 0 / 0 |
| unparsable RT values | 0 / 560,084 |
| distinct RT strings | 8,369 (RT is not constant) |
Because the row order and the first seven columns are identical, row_index alone is a
complete join key to MSnLib.csv. The exported table is
msnlib_rt.csv.gz — 1,483,069 bytes, SHA-256
994053612db874f7ac7985f278e04cc3463f3b93cd649a195bd167c4c6c7d3d8, 560,084 data rows,
columns row_index,rt, gzipped only (no plain twin) to keep the package compact.
6. Frozen table hashes
SHA-256 of the plain CSV files (the .csv.gz twins decompress to exactly these bytes):
| file | rows | bytes | SHA-256 |
|---|---|---|---|
formula_split.csv |
21,107 | 424,350 | fcc44d1996d25306c884a6f8da30c1447fbe74f93c6fa12a3f271c0475a704b8 |
row_formula_fold.csv |
560,084 | 13,351,630 | ac6113867fdda683304533f097fc7287c13271a2deac8e792d1316dcf00264ff |
test_spectra.csv |
57,437 | 7,751,575 | f2a870ba8ac9a54a36feaf1ecc12929ad9250ade2d082dc31454028c4b66b548 |
val_spectra.csv |
55,980 | 7,421,554 | f4fa5e0f8875991bf9df2bcb67a05437271ee18c317f33d9108f3ec28a887a82 |
test_molecules_voting.csv |
5,002 | 276,185 | edad6ec7d6b6f9fc4763deac5245207aee767c78661532621c87acc5a9b1ee07 |
test_molecules_voting_canonical_view.csv |
4,888 | 269,502 | 9fcd16ff4159e665833ea145848f94bee7c44115f4a858dd75fe486f15e92bd0 |
Gzipped-only companion: msnlib_rt.csv.gz — 560,084 rows, 1,483,069 bytes, SHA-256
994053612db874f7ac7985f278e04cc3463f3b93cd649a195bd167c4c6c7d3d8.
7. Voting-unit definitions: official 5,002 source-SMILES groups vs 4,888 canonical groups
The official multiple-spectrum voting unit is the MSnLib source SMILES string. The test fold contains 5,003 distinct source SMILES strings and 4,889 distinct RDKit canonical isomeric molecules:
- grouping by the source SMILES string gives 5,002 groups with ≥2 spectra covering
57,436 spectra (one source string occurs in only one spectrum), and this grouping is
member-for-member identical to the published repository table that defines
n_molecules = 5002; it is shipped astest_molecules_voting.csv; - grouping by RDKit canonical isomeric SMILES gives 4,888 groups covering the same
57,436 spectra, leaving exactly one single-spectrum molecule
(
CC(C)(C)OC(=O)NCC1(CC(=O)O)CCCCC1); it is shipped astest_molecules_voting_canonical_view.csvand is an alternative chemical-deduplication view, not the official voting unit.
The difference is a property of the source library: 114 canonical molecules are written with more than one SMILES string among their test spectra. No data was altered to force either count.
8. Replay from MSnLib.csv
build_split_a.py replays the complete split (formula computation, frozen fold assignment,
all six tables) from MSnLib.csv. It was run read-only in the isolated data-preparation environment
(RDKit 2026.03.5) without an output directory:
python3 build_split_a.py --csv datasets/MSnLib/MSnLib.csv
Result: all 12 count checks passed, all 6 table SHA-256 values matched the frozen files, and the script exited 0. Transcript:
[PASS] n_data_rows: 560,084 (expected 560,084)
[PASS] n_unique_formula: 21,107 (expected 21,107)
[PASS] n_formula_train: 16,885 (expected 16,885)
[PASS] n_formula_val: 2,110 (expected 2,110)
[PASS] n_formula_test: 2,112 (expected 2,112)
[PASS] n_spectra_train: 446,667 (expected 446,667)
[PASS] n_spectra_val: 55,980 (expected 55,980)
[PASS] n_spectra_test: 57,437 (expected 57,437)
[PASS] n_voting_groups_official: 5,002 (expected 5,002)
[PASS] n_voting_spectra_official: 57,436 (expected 57,436)
[PASS] n_voting_groups_canonical: 4,888 (expected 4,888)
[PASS] n_voting_spectra_canonical: 57,436 (expected 57,436)
[PASS] formula_split.csv: 424,350 bytes sha256 fcc44d1996d25306c884a6f8da30c1447fbe74f93c6fa12a3f271c0475a704b8
[PASS] row_formula_fold.csv: 13,351,630 bytes sha256 ac6113867fdda683304533f097fc7287c13271a2deac8e792d1316dcf00264ff
[PASS] test_spectra.csv: 7,751,575 bytes sha256 f2a870ba8ac9a54a36feaf1ecc12929ad9250ade2d082dc31454028c4b66b548
[PASS] val_spectra.csv: 7,421,554 bytes sha256 f4fa5e0f8875991bf9df2bcb67a05437271ee18c317f33d9108f3ec28a887a82
[PASS] test_molecules_voting.csv: 276,185 bytes sha256 edad6ec7d6b6f9fc4763deac5245207aee767c78661532621c87acc5a9b1ee07
[PASS] test_molecules_voting_canonical_view.csv: 269,502 bytes sha256 9fcd16ff4159e665833ea145848f94bee7c44115f4a858dd75fe486f15e92bd0
A local replay needs MSnLib.csv (752,707,651 bytes, SHA-256 as in §2) and RDKit
2026.03.5. With a different RDKit patch release, the tables that carry canonical
strings can differ textually while every count above still matches; the script reports that
as a DIFF with an explanatory message (or a warning under --lenient-rdkit) and the
formula tables are unaffected.
9. Simple structural checks
# rows
wc -l formula_split.csv row_formula_fold.csv test_spectra.csv val_spectra.csv \
test_molecules_voting.csv test_molecules_voting_canonical_view.csv
# 21108 / 560085 / 57438 / 55981 / 5003 / 4889 (incl. header)
# gzip -dc msnlib_rt.csv.gz | wc -l -> 560085 (incl. header)
# csv.gz twins are byte-identical after decompression
for f in *.csv; do cmp <(gzip -dc "$f.gz") "$f" || echo "MISMATCH $f"; done
# formula-level uniqueness
python3 - <<'PY'
import csv, collections
fold = {}
for r in csv.DictReader(open("formula_split.csv")):
fold[r["formula"]] = r["fold"]
print(len(fold), collections.Counter(fold.values()))
PY
10. What could not be verified from this directory alone
- The actual peak arrays (
mzs/intensities) are not shipped; they live inMSnLib.csv. The row pointers and the row → formula → fold mapping inrow_formula_fold.csvare the authoritative link back to the spectra. - The exact physical row order of
MSnLib.csv(which follows the frozen UltraMS conversion of the MSnLib release records); the package depends on the row pointers, not on reconstructing that order from the release files. - The historical Figure-3 analysis artifacts themselves; only the published repository voting-group table was cross-checked (§5.3).
11. Version
Split A release 1.0.0, generated 2026-11-04. Any change to the tables, the fold
assignment or the formula computation invalidates the hashes above and requires a new
version directory.