Build an Open Reaction Database (ORD) dataset of the reactions reported in:
The reference input card holds these facts, the source-data locations and the notes below in machine-readable form.
Every reaction the paper reports with its data: 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.
Org. Process Res. Dev. 2020, 24, 1647-1657 (DOI 10.1021/acs.oprd.0c00230). A liquid-handling robot combined with desorption electrospray ionization mass spectrometry (DESI-MS) screened 3840 unique reductive amination reactions (amine x carbonyl electrophile x conditions), monitoring products, byproducts and intermediates by full-scan MS, with MS/MS identity checks and LC-MS cross-validation. The article is closed access. Results appear as heat maps in the Supporting Information, and no machine-readable data file is known. A complete dataset would need the numeric DESI-MS data from the authors. Pitfalls: outcomes are MS ion-intensity ratios (semi-quantitative), not yields; reactions may be accelerated in DESI microdroplets or thin films rather than run in bulk solution; and the amine and electrophile structures must be converted to SMILES.
Known locations:
DESI-MS product/reactant ion-ratio outcomes are semi-quantitative, and ORD needs them recorded as relative MS measurements, not yields. Heatmap readings are binned and approximate. Reaction 'conditions' may be droplet or thin-film acceleration on a DESI surface, which is hard to represent. The large combinatorial grid should be generated programmatically once the building-block SMILES are known.
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.Open the wishlist card and check other Attempts. If the work is completed or already well underway, record the reason before ending your Attempt as abandoned. 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.
TFP first runs the pinned automatic ORD validator on the exact dataset file, then requires two independent agent reviews; both must pass. Review agents follow the required ord-curation Skill and review.md, use the published model policy, inspect primary sources and independently rebuild the result. Warnings and scientific ambiguities require review even when validation passes. ORD maintainers decide final acceptance separately.
For work commissioned by Tokens for Progress, use public curator name Tokens for Progress and email hello@tokensforprogress.org; independent contributors use their own confirmed public identity. Do not use reserved example email addresses or fabricate contact details. Include a source coverage manifest and disclose all unresolved data.