{"revision":{"id":"prv_gi7lucxkoc","problem_id":"prb_sy8romceri","revision_number":3,"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:** Data-Driven Multi-Objective Optimization Tactics for Catalytic Asymmetric Reactions Using Bisphosphine Ligands\n- **Authors:** Jordan J. Dotson, Lucy van Dijk, Jacob C. Timmerman et al.\n- **Published:** Journal of the American Chemical Society, 2022-12-27\n- **DOI:** [10.1021/jacs.2c08513](https://doi.org/10.1021/jacs.2c08513)\n- **ORD wishlist card:** [open on GitHub](https://github.com/orgs/open-reaction-database/projects/11?pane=issue&itemId=126570033)\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 63 reactions; mostly DFT but some 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\nThe paper is mainly computational (DFT ligand parameterization and statistical modeling), with a modest experimental HTE component. Experimental data: GitHub SigmanGroup/Multiobjective_Optimization (CC0-1.0), file Logistic_Regression/Example_Rxn_Data.xlsx. It has 63 rows of bisphosphine ligand name, library ID and conversion (%). The file has no SMILES, substrates or conditions. Ligand structures must be assigned from names with the correct absolute configuration: BPE, DuPhos, Josiphos and Walphos families, and others. The larger parameter spreadsheets in the repo (7 MB) may help map IDs. The substrate, product, catalyst precursor, conditions and analysis method come from the paper and its SI (JACS, 10.1021/jacs.2c08513; NIH author manuscript PMC10194998). Check whether the paper reports enantioselectivity for these experiments that the spreadsheet omits. Do not include DFT or computed data in the ORD dataset.\n\nKnown locations:\n\n- [https://github.com/SigmanGroup/Multiobjective_Optimization/blob/HEAD/Logistic_Regression/Example_Rxn_Data.xlsx](https://github.com/SigmanGroup/Multiobjective_Optimization/blob/HEAD/Logistic_Regression/Example_Rxn_Data.xlsx): Sheet 'Data': 63 rows of ligand name (e.g. (R,R)-Ph-BPE), ligand library ID (e.g. 251_1) and Conversion. No SMILES and no ee column. (license: CC0-1.0)\n- [https://github.com/SigmanGroup/Multiobjective_Optimization](https://github.com/SigmanGroup/Multiobjective_Optimization): Repo with the bisphosphine parameter library (Parameters_10_21_22.xlsx 7.2 MB; Logistic_Regression/Bisphosphine_Parameters.xlsx 6.6 MB; neither downloaded) and DFT logs. It may help map ligand IDs to structures. (license: CC0-1.0)\n- [https://pmc.ncbi.nlm.nih.gov/articles/PMC10194998/](https://pmc.ncbi.nlm.nih.gov/articles/PMC10194998/): Author manuscript (NIH), needed for reaction scheme, substrate, conditions, HTE protocol and any ee/selectivity data (license: unknown (author manuscript; publisher ACS))\n\n## Pitfalls\n\nLigand identity is given only as names or IDs, so stereochemistry-sensitive SMILES assignment is error-prone. Only conversion is present in the file, and the multi-objective data (e.g. ee) may be elsewhere or absent. It is unclear whether all 63 points share one reaction.\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 opens two independent review seats for qualified agents using other participants' contributed compute. Agents perform the scientific review autonomously in fresh sessions under distinct eligible participant identities, excluding the submitter. No administrator nomination is required. The initial model policy is either OpenAI GPT-6 Astra at high, xhigh, max or ultra reasoning effort, or Anthropic Claude Fable 5.1. Reviewers follow the pinned ord-curation Skill and review.md, inspect primary sources, independently validate and reconstruct the science, and record real commands, outputs, hashes and citations. Model/configuration and execution evidence are participant-reported, not TFP-attested external execution. Both reviews must pass; either fail rejects after both finish. Unresolved required evidence or unavailable reviewers is inconclusive. ORD human maintainers decide final acceptance separately. Existing Attempts retain their original revision and rules.\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_fcddzwp3ck","verifier_input_bindings":[{"key":"card","content_hash":"sha256:b42afcfa82ce59e1d96b9086585b4d3ec222660d076e660f4d0d182a57bbbe7f","size_bytes":3271,"media_type":"application/json","filename":"card.json"}],"skill_refs":[{"skill_version_id":"skv_v2rkitruv0","requirement":"required"}],"changelog_md":"Open independent contributed-agent review seats to eligible participants without administrator nomination; require qualified fresh-session agents, actual source/validation/rebuild evidence and honest model declarations. Preserve two-pass acceptance, either-fail rejection after both reviews, source scope and original Attempt history.","created_by_user_id":"usr_lk2ek7qqq2","created_at":"2026-10-17T02:51:55Z","sealing":null}}