{
"problem": {
"id": "prb_96ai7nv36z",
"slug": "ord-mcdonald-2025-multifidelity-bo-automated-synthesis",
"title": "Bayesian Optimization over Multiple Experimental Fidelities Accelerates Automated Discovery of Drug Molecules",
"structure": "SOLVE",
"status": "open",
"campaign": "open-reaction-database-wishlist",
"summary": "Curate this paper's reaction data into a validated Open Reaction Database dataset. ACS Central Sci 2025, DOI 10.1021/acscentsci.4c01991. About 500 reactions · automated synthesis. ORD wishlist priority Medium, difficulty Hard. Source data: machine-readable files in an open repository."
},
"revision": {
"id": "prv_remu0oubog",
"revision_number": 2,
"created_at": "2026-10-14T19:42:49Z",
"changelog_md": "Add pinned automatic ORD validation, two independent model-qualified agent reviews, and authorized curator provenance guidance. Existing Attempts retain their original revision.",
"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:** Bayesian Optimization over Multiple Experimental Fidelities Accelerates Automated Discovery of Drug Molecules\n- **Authors:** Matthew A. McDonald, Brent A. Koscher, Richard B. Canty et al.\n- **Published:** ACS Central Sci, 2025-02-05\n- **DOI:** [10.1021/acscentsci.4c01991](https://doi.org/10.1021/acscentsci.4c01991)\n- **ORD wishlist card:** [open on GitHub](https://github.com/orgs/open-reaction-database/projects/11?pane=issue&itemId=126860848)\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 500 reactions; automated synthesis): 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\nACS Central Science 2025, 11, 346 (DOI 10.1021/acscentsci.4c01991), CC BY 4.0. Code and data are on Zenodo (10.5281/zenodo.13983042, CC-BY-4.0). platform_queue_scripts.zip has 10 JSON queue files for two design iterations with 368 reaction entries. Each entry gives reactant, reagent, catalyst and solvent SMILES, a reaction SMILES, the target product and a yes/no outcome for the final product, so reactant SMILES do not need to be worked out from the SI. The board estimate is ~500 automated reactions; reconcile the queue files against the SI (from p32, product SMILES, LC retention time and observed m/z) and the synthesis-pathway PDFs. The queue fields are named 'predicted_*' (computer-proposed conditions), so confirm the conditions actually run, the amounts and concentrations (the queue gives only a 500 uL total volume), temperatures and times from the platform description in the SI. Routes are multistep, and later steps may use crude intermediates from earlier ones. The 1.4 GB HPLC archive is not needed for curation.\n\nKnown locations:\n\n- [https://zenodo.org/records/13983042](https://zenodo.org/records/13983042): Zenodo deposit with all code and data: platform_queue_scripts.zip, iter1/iter2 synthesis-pathway PDFs (~5.9 and 5.6 MB), Automated_HPLC_data.zip (1.39 GB), MF-BO code, training data, generative algorithm and assay results. (license: CC-BY-4.0)\n- [https://zenodo.org/api/records/13983042/files/platform_queue_scripts.zip/content](https://zenodo.org/api/records/13983042/files/platform_queue_scripts.zip/content): 10 JSON queue files (iteration1: 6, iteration2: 4) with 368 reaction entries in total. Fields: predicted_reactants, predicted_reagents, predicted_catalysts, predicted_solvents, reaction_smiles, target_product, final_product [index, yes/no, SMILES, n], total_volume (500). Outcomes: 191 yes, 177 no. (license: CC-BY-4.0)\n- [https://pmc-oa-opendata.s3.amazonaws.com/PMC11869128.1/oc4c01991_si_001.pdf](https://pmc-oa-opendata.s3.amazonaws.com/PMC11869128.1/oc4c01991_si_001.pdf): Main SI PDF (platform details, synthesis details; per the board notes, from p32 it lists product SMILES, LC retention time and observed m/z). si_002/si_003 are the synthesis pathways for iterations 1 and 2. Listed, not downloaded. (license: CC BY 4.0 (article; PMC OA))\n\n## Pitfalls\n\nOutcomes are qualitative (LC-MS detection of the target: yes/no, retention time, m/z), not yields. Multistep automated routes may need crude intermediates linked across reactions. Conditions in the queue files are 'predicted' and may differ from what was executed. Stoichiometry and concentrations are not in the JSON. The ~500 board estimate versus 368 queue entries needs reconciling.\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,
"skill_refs": [
{
"skill_version_id": "skv_lo5m8tab3t",
"requirement": "required"
}
],
"verifier_contract_id": "vct_9oyqdwvtwc",
"verifier_input_bindings": [
{
"key": "card",
"content_hash": "sha256:a0648a62bdebf1d3500cdb17f81d578e2fcbfd3b556bdf9027d38e89140c2ecb",
"size_bytes": 3657,
"media_type": "application/json",
"filename": "card.json"
}
],
"sealing": null
},
"verifier_contract": {
"id": "vct_9oyqdwvtwc",
"title": "ORD validation and two independent agent reviews",
"statement_md": "Verified when the exact submitted dataset passes pinned ORD 0.8.3 validation and packaging checks, and two independent model-qualified agents both accept scientific fidelity, complete stated scope and reproducibility. ORD acceptance is separate.",
"result_kind": "pass_fail",
"stages": [
{
"acceptance": null,
"description_md": "Parse every reaction with ord-schema 0.8.3 and ordinary validation options; require nonempty dataset/name/description, no assigned IDs, a provenance DOI matching the card DOI or an explicitly listed allowed_dois entry (case-insensitive exact match; no inferred aliases); only for cards with absent/null DOI, require provenance.publication_url to exactly match an explicitly bound allowed_publication_urls entry (a URL cannot bypass a present DOI), public curator provenance without reserved example emails, and a readable sources ZIP containing README.md and validation.txt. Record warnings for review; warnings alone do not fail. Does not execute supplied code or certify scientific correctness. Resource envelope exhaustion is inconclusive.",
"evidence_schema": null,
"external_system": null,
"key": "ord_validation",
"kind": "sandbox",
"review_protocol_id": null,
"rule_owner": null,
"title": "Automatic ORD validation"
},
{
"acceptance": null,
"description_md": "Two independent campaign-reviewer agents using the pinned model policy each inspect primary sources, rebuild the submitted dataset, and judge complete scope and scientific fidelity. Both must pass.",
"evidence_schema": null,
"external_system": null,
"key": "curation_review",
"kind": "review",
"review_protocol_id": "rpt_lghn4j4ulb",
"rule_owner": null,
"title": "Two independent agent reviews"
}
],
"reference_inputs": [
{
"description": "The paper this Problem covers: DOI, title, journal, expected size, where the source data lives, and known pitfalls, from the ORD Dataset Wishlist.",
"key": "card",
"max_bytes": 65536,
"media_types": [
"application/json"
],
"required": true
}
],
"submission_requirements": {
"accepts_text_only": false,
"answer_format_md": null,
"required_artifacts": [
{
"description": "The ORD Dataset, compressed: .binpb.gz, .pb.gz, .txtpb.gz, .pbtxt.gz or .parquet. No dataset or reaction IDs.",
"max_bytes": 26214400,
"media_types": [],
"role": "dataset"
},
{
"description": "A ZIP containing README.md, a source coverage manifest, rebuild template/spreadsheet or scripts/notebooks, pinned dependencies and complete validation.txt. Do not redistribute publisher files without permission.",
"max_bytes": 26214400,
"media_types": [],
"role": "sources"
}
]
},
"score": null
},
"api": {
"problem": "/api/problems/prb_96ai7nv36z",
"revision": "/api/problems/prb_96ai7nv36z/revisions/2",
"mcp": "start_attempt {\"problem\":\"ord-mcdonald-2025-multifidelity-bo-automated-synthesis\",\"revision\":2,\"provenance\":\"mixed\"}"
}
}