Curate this paper into an ORD dataset

Build an Open Reaction Database (ORD) dataset of the reactions reported in:

• Paper: Generality-driven optimization of enantio- and regioselective catalysis by high-throughput experimentation and machine learning
• Authors: Terim Seo, Donghun Kim, Shinwon Ham et al.
• Published: ChemRiv, 2025-04-23
• DOI: 10.26434/chemrxiv-2025-n3gff
• 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 500 reactions; HTE): 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

HTE and machine learning for enantio- and regioselective mono-reduction of 1,2-dicarbonyls, about 500 reactions. The ORD card cites the ChemRxiv preprint (10.26434/chemrxiv-2025-n3gff, CC BY-NC-ND 4.0), where the data is in SI Tables S2-S4 as plate images. Values would need image extraction, and compound SMILES must be generated from structures. A peer-reviewed version has been published in Angew. Chem. Int. Ed. (10.1002/anie.202519425); check whether its SI provides the data in a more usable form. The dataset should cite the published DOI (and the preprint). Obtaining numeric data (e.g. ee/regioselectivity/conversion tables) from the authors would substantially reduce extraction error.

Known locations:

• https://doi.org/10.26434/chemrxiv-2025-n3gff: ChemRxiv preprint and SI (Tables S2-S4 as plate images); the ChemRxiv API was blocked by a Cloudflare challenge (license: CC BY-NC-ND 4.0 (Crossref, preprint))
• https://doi.org/10.1002/anie.202519425: Published version: Angew. Chem. Int. Ed. 2025, 65(1), 'Generality-Driven Optimization of Enantio- and Regioselective Mono-Reduction of 1,2-Dicarbonyls by HTE and Machine Learning' (found via Crossref; page not fetched) (license: Wiley terms and conditions (Crossref VOR))

Pitfalls

Outcomes include enantioselectivity (ee) and regioselectivity, which need stereo-aware product SMILES. Values read from plate images carry transcription uncertainty. Preprint and published SI may disagree.

Deliver

• dataset: the ORD Dataset, compressed (.binpb.gz, .pb.gz, .txtpb.gz, .pbtxt.gz or .parquet), citing the DOI above in every reaction's provenance, with no dataset or reaction IDs.
• sources: a .zip with a README.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, and validation.txt, the output of ORD's validator (ord-schema 0.8.3) on the dataset file.

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.