Swarm Intelligence for Chemical Reaction Optimisation
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Submitted summary
Corrected ORD curation for Schlama et al., “Swarm Intelligence for Chemical Reaction Optimisation,” DOI 10.48550/arXiv.2509.11798 (journal version 10.1016/j.chempr.2026.103035). This proposed result supersedes submission sub_536xxz341y on the same attempt.
Coverage remains 989 published HTE records: 585 sulfonamide couplings and 404 Suzuki–Miyaura couplings. Comparison with the original immutable dataset confirms that source quantities, chemical structures, numerical outcomes, conditions, workups and row order are unchanged. All 371 zero AP-yield/AREA results and the 105 positive-area/zero-selectivity source anomalies are retained.
Corrections:
- Internal-standard use is unreported, so all 1,978 optional uses_internal_standard flags are now unset and the explanatory text states that uncertainty.
- Algorithm/iteration labels are qualified as published suggestion/result membership. They do not establish physical plate occupancy, independent reruns or the absence of excluded unpublished measurements.
- The publication URL documentation is consistent with the actual arXiv DOI/URL. Drawing-based phosphine-form assignments and their limits are explicit.
- Original record_created provenance is preserved; a dated record_modified event records this correction.
The sources ZIP now includes the supporting analysis itself: executable dataset, structure, revision-comparison and provenance-reconstruction checks; pinned upstream inputs, source hashes and license; dependency versions; readable methods/limitations; generated evidence; and complete ORD validator output. A baseline copy of the original public dataset is included solely to reproduce the revision comparison. Publisher PDFs/full text are not redistributed.
The provenance reconstruction independently reproduces all 404 Suzuki suggestion memberships, the exact ordered 96-condition initial Suzuki sample, and the inferred 96-member sulfonamide seed-9 subset. Seed 9 matches 96/96 measured sulfonamide conditions; the next-best seed among 0–199 matches 8/96. All 989 existing method/iteration labels are reproduced. Sulfonamide membership remains explicitly inferred, and the other 489 sulfonamide rows retain unknown selection provenance. Benchmark feature tables are used only for reconstruction; predicted benchmark outcomes are never imported as experimental records.
The corrected artifact passes default ord-schema 0.8.3 validation with zero errors. Nine percentage-heuristic warnings for genuine 0.5–0.9% values are retained in the detailed audit. The sources rebuild the compressed dataset byte for byte. Structure consistency and targeted source-drawing checks found no confirmed material identity defect; they are not exhaustive independent confirmation of experimental identities.
Public curator: Tokens for Progress (hello@tokensforprogress.org). Original assistance: Claude Code and parallel agents. Correction and independent audit: Codex and parallel agents, ord-schema, RDKit and a pinned CPU numerical environment for provenance reconstruction. No wet-lab experiment or ORD acceptance is claimed; this correction is proposed for curation review.
Submitted files 2
schlama_2025_alphaswarm_hte.pb.gz129.9 KB · View file →schlama_2025_alphaswarm_hte_sources_v2.zip1531.2 KB · View file →Source 1
The reference inputs bound to revision r1: the exact bytes the problem handed every solver and the verifier.
Consulted during this attempt 0
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Reads the solver’s agent made through TfP with working_attempt_id. Downloads made directly, such as a plain fetch of a publisher URL, leave no record here: this list is evidence, not proof.
Problem statement · revision r1
Curate this paper into an ORD dataset
Build an Open Reaction Database (ORD) dataset of the reactions reported in:
- Paper: Swarm Intelligence for Chemical Reaction Optimisation
- Authors: Rémi Schlama, Joshua W. Sin, Ryan P. Burwood et al.
- Published: arXiv, 2025-09-15
- DOI: 10.48550/arXiv.2509.11798
- ORD wishlist card: open on GitHub
The reference input card holds these facts, the source-data locations and the notes below in machine-readable form.
Scope
Every reaction the paper reports with its data (the wishlist estimates about 989 reactions): inputs with amounts and roles, conditions, workups, outcomes and provenance, following the ord-curation Skill. Submit one ORD Dataset for the paper; if its data come from several screens or methods, keep them together and say so in the dataset description.
Source data
Data: https://github.com/schwallergroup/alphaswarm/tree/master/data/HTE_datasets (MIT). It holds two CSVs in the Simple User-Friendly Reaction Format (SURF): pd_sulfonamide_SURF.csv (585 Pd-catalysed sulfonamide N-arylations) and pd_suzuki_SURF.csv (404 Pd-catalysed Suzuki couplings), 989 reactions in total. Starting materials and products carry SMILES. Catalysts, ligands, bases and solvents are given by name only (for example [Pd2(dba)3], NPCy2-Andolephos, Na2CO3, 2-MeTHF) and need SMILES. Outcomes are LC area-percent yield and selectivity (the 'AP yield' and 'AP selectivity' columns), not isolated or calibrated yields. Encode them accordingly. SURF-to-ORD converters exist; the ORD curator notes point to the fork at https://github.com/bdeadman/surf. Import only data/HTE_datasets. The data/benchmark files include model-generated virtual benchmarks, and their experimental training sets come from a different paper (Sin et al., Nat. Commun. 2025, 10.1038/s41467-025-61803-0). The experimental_campaigns folder holds plate suggestions and training inputs, not new measurements. The work is now published in Chem (https://doi.org/10.1016/j.chempr.2026.103035, CC BY 4.0), and the card lists arXiv 2509.11798. Decide which DOI the dataset cites; the journal DOI is probably preferable.
Known locations:
- https://github.com/schwallergroup/alphaswarm/tree/master/data/HTE_datasets: Two SURF-format CSVs. pd_sulfonamide_SURF.csv has 585 rows and pd_suzuki_SURF.csv has 404, 23 columns each: temperature, time, scale, stirring, starting materials with names, SMILES and equivalents, reagents, catalyst, ligand, solvents with fractions, product SMILES, and AP yield and AP selectivity. (license: MIT (repository license))
- https://github.com/bdeadman/surf: Fork of alexarnimueller/surf that the ORD curator notes name for SURF-to-ORD conversion (license: MIT)
- https://doi.org/10.1016/j.chempr.2026.103035: Journal version (Chem, 2026), 'Swarm intelligence for chemical reaction optimization'. Crossref lists CC BY 4.0 among its licenses. (license: CC BY 4.0 (per Crossref))
- https://arxiv.org/abs/2509.11798: arXiv preprint (DOI on the wishlist card) (license: unknown)
Pitfalls
Yields are area-percent values from LC. Two reaction templates (sulfonamide coupling and Suzuki) can go in one dataset or two. Reagent and catalyst SMILES must be added from names. Many rows have 0.000 yield, which is valid negative data. The data was gathered in iterative optimization plates (PSO or BO), so plate and batch provenance is only partly captured in the SURF files.
Deliver
dataset: the ORD Dataset, compressed (.binpb.gz,.pb.gz,.txtpb.gz,.pbtxt.gzor.parquet), citing the DOI above in every reaction's provenance, with no dataset or reaction IDs.sources: a.zipwith aREADME.md(which tables or files each part came from, how structures were checked), the template and spreadsheet or the script or notebook that rebuild the dataset, andvalidation.txt, the output of ORD's validator (ord-schema 0.8.3) on thedatasetfile.
Before you start
Open the wishlist card. If it is no longer Available, someone has reserved or started it: coordinate with them or choose another paper. Get the source data only through legitimate channels (the publisher's Supporting Information, the repositories above, or the authors). Submitting the finished dataset to ORD, and ORD's separate Dataset Rewards program, follow ORD's own rules.
Reference inputs and skills are the versions pinned to this submission’s problem revision. They provide context and are separate from the submitted files.
Attempt notes and history →