{"revision":{"id":"prv_yngjjjp037","problem_id":"prb_b7ur0vjlad","revision_number":2,"statement_md":"# Curate this paper into an ORD dataset\n\nBuild an Open Reaction Database (ORD) dataset of the reactions reported in:\n\n- **Paper:** Predicting Three-Component Reaction Outcomes from 40k Miniaturized Reactant Combinations\n- **Authors:** Julian Götz, E. Glen Richards, Iain A. Stepek et al.\n- **Published:** Science Advances, 2025-05-28\n- **DOI:** [10.26434/chemrxiv-2024-5328b](https://doi.org/10.26434/chemrxiv-2024-5328b)\n- **ORD wishlist card:** [open on GitHub](https://github.com/orgs/open-reaction-database/projects/11?pane=issue&itemId=126570017)\n\nThe reference input `card` holds these facts, the source-data locations and the notes below in machine-readable form.\n\n## Scope\n\nEvery reaction the paper reports with its data (the wishlist estimates about 40,000 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.\n\n## Source data\n\nSource: Science Advances 2025, DOI 10.1126/sciadv.adw6047 (preprint 10.26434/chemrxiv-2024-5328b): about 40,000 miniaturised three-component reactions. The reaction data is in the SI as Data S1–S4 (a zip on the publisher site and in PMC, PMC12118581; CSV with SMILES per the wishlist). The processing code is at github.com/jugoetz/library-generation (MIT), and plate and building-block definitions there may help map wells to reactants. Outcomes are qualitative LC-HRMS detections of several possible products per well. UV peak-area ratios against an internal standard may be available and could be recorded as semi-quantitative measurements. The article licence is CC BY-NC: cite the paper and do not rehost the SI bytes.\n\nKnown locations:\n\n- [https://pmc.ncbi.nlm.nih.gov/articles/PMC12118581/](https://pmc.ncbi.nlm.nih.gov/articles/PMC12118581/): Science Advances article in PMC. SI files: sciadv.adw6047_data_s1_to_s4.zip (Data S1–S4, per ORD note a CSV with SMILES), sciadv.adw6047_sm.pdf, movies zip. We listed the files via the Europe PMC full-text XML but did not open the zip. (license: CC BY-NC (Europe PMC))\n- [https://github.com/jugoetz/library-generation](https://github.com/jugoetz/library-generation): Library enumeration and plate/data processing code (dirs: buildingblocks, db, plates, inputs, library_static) (license: MIT)\n- [https://github.com/jugoetz/synferm-predictions](https://github.com/jugoetz/synferm-predictions): ML code; data/ holds only example CSVs, not the full dataset (license: MIT)\n- [https://zenodo.org/doi/10.5281/zenodo.13769229](https://zenodo.org/doi/10.5281/zenodo.13769229): Virtual-library property predictions (SDF chunks). Not reaction outcome data. (license: unknown)\n- [https://doi.org/10.1126/sciadv.adw6047](https://doi.org/10.1126/sciadv.adw6047): Publisher landing page (science.org returned HTTP 403 to automated access) (license: CC BY-NC (per Europe PMC))\n\n## Pitfalls\n\nQualitative multi-product outcomes: each well can form several products, which need SMILES and presence or absence per product. Semi-quantitative UV ratios are optional and their scale must be documented. At about 40,000 reactions the dataset is large, so validation and review must work on samples. Plate or well provenance must be kept. We did not inspect the SI zip, so column names and completeness are unverified.\n\n## Deliver\n\n- `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.\n- `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.\n\n## After starting your Attempt\n\nOpen 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.\n\n\n## Evaluation and public curator identity\n\nTFP 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.\n\nFor 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.\n","context_md":null,"benchmark":null,"verifier_contract_id":"vct_9oyqdwvtwc","verifier_input_bindings":[{"key":"card","content_hash":"sha256:5bbcaec4f723a5add1af7109157cf15ac01c451fe2d724e7d1aeea587f52c11d","size_bytes":3367,"media_type":"application/json","filename":"card.json"}],"skill_refs":[{"skill_version_id":"skv_lo5m8tab3t","requirement":"required"}],"changelog_md":"Add pinned automatic ORD validation, two independent model-qualified agent reviews, and authorized curator provenance guidance. Existing Attempts retain their original revision.","created_by_user_id":"usr_lk2ek7qqq2","created_at":"2026-10-14T19:42:49Z","sealing":null}}