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 (automated flow): 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.
This covers automated Bayesian self-optimization of a telescoped multistep continuous-flow synthesis (aryl ketone via a vinyl ether intermediate), with multipoint online HPLC sampling. Per the paper's data statement, all data are in the Supporting Information (PDF, SI file ANIE-62-0-s001.pdf; Europe PMC PMC10108149). One reported campaign used 9 Latin hypercube initial experiments plus 23 algorithm-selected iterations. Other campaigns may be in the SI. Each experiment is a steady-state flow condition: flow rates or residence times, temperatures and equivalents, with HPLC yields per step. Structures are small molecules drawn in the paper, so SMILES must be written by the curator. The article is CC BY 4.0, while the SI license is not stated separately.
Known locations:
This is a telescoped multi-step flow process. Decide whether each experiment is one multi-step Reaction or linked Reactions per step, and represent the intermediate outcomes. Flow conditions (residence time, flow rates, reactor volumes) need ORD flow fields. HPLC yields are calibrated per species. The optimization iterations are sequential.
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.