{
"problem": {
"id": "prb_5sa1dgmzdx",
"slug": "ord-angello-2022-suzuki-closed-loop",
"title": "Closed-loop optimization of general reaction conditions for heteroaryl Suzuki-Miyaura coupling",
"structure": "SOLVE",
"status": "open",
"campaign": "open-reaction-database-wishlist",
"summary": "Curate this paper's reaction data into a validated Open Reaction Database dataset. Science 2022, DOI 10.1126/science.adc8743. Optimisation. Source data: machine-readable files in an open repository."
},
"revision": {
"id": "prv_f1z6myzblf",
"revision_number": 1,
"created_at": "2026-09-25T19:27:21Z",
"changelog_md": null,
"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:** Closed-loop optimization of general reaction conditions for heteroaryl Suzuki-Miyaura coupling\n- **Authors:** Nicholas H. Angello, Vandana Rathore, Wiktor Beker et al.\n- **Published:** Science, 2022-10-27\n- **DOI:** [10.1126/science.adc8743](https://doi.org/10.1126/science.adc8743)\n- **ORD wishlist card:** [open on GitHub](https://github.com/orgs/open-reaction-database/projects/11?pane=issue&itemId=126570036)\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 (Optimisation): 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\nPrimary source: Zenodo record 10.5281/zenodo.7106075 (CC-BY-4.0). Use 'Figure 3C_experimental_data_tab_delimited.csv' (tab-delimited despite the .csv name, 454 rows). It has SMILES for the MIDA boronate, bromide and product, plus categorical solvent/base/ligand/Pd source, temperature, yield as a fraction (0-1) and closed-loop round_id. Rows come in A/B replicate pairs (experiment_id like 1A/1B). Quantities, concentrations, reaction time, the solvent ratio (listed only as '1,4-dioxane:water') and the yield-determination method must come from the paper's SI. Do not include 'Figure 3C_literature_data_colon_delimited.csv': it is literature-mined data, not experiments from this paper. Figure 4 xlsx files may contain additional scope or validation reactions under the optimized conditions. Include them only if they are experiments reported in the paper. The article is not open access, but the data record is CC-BY-4.0.\n\nKnown locations:\n\n- [https://zenodo.org/records/7106075](https://zenodo.org/records/7106075): Tabulated data behind Figures 2-4. 'Figure 3C_experimental_data_tab_delimited.csv' (82 KB, 454 rows x 16 columns) has SMILES for the MIDA boronate, bromide and product, plus solvent, base, ligand, Pd source, temperature, yield (as a fraction), round_id and a smiles_ok flag. Figure 4*.xlsx files… (license: CC-BY-4.0)\n- [https://zenodo.org/records/6517012](https://zenodo.org/records/6517012): Associated code release (Nanotekton/hangman-v1.0) for the ML and optimization. Not needed for reaction data. (license: other-open (per Zenodo metadata))\n- [https://doi.org/10.1126/science.adc8743](https://doi.org/10.1126/science.adc8743): Science article and SI, needed for amounts, concentrations, reaction times, the dioxane:water ratio and the analytical method (license: closed (publisher))\n\n## Pitfalls\n\nYields are fractions, not percent. Replicate pairs should become separate Reactions or a documented replicate structure. MIDA boronate SMILES contain charged, stereo-tagged tetracoordinate boron ([B-], [B@@-]) and should be checked for RDKit parsing. A smiles_ok column flags problematic rows. Solvent is a mixture with the ratio given only in the SI. Reaction-time and amount details are not in the data file. The closed-loop rounds span the optimization campaign, so there are many conditions across many substrate pairs.\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## Before you start\n\nOpen the wishlist card. If it is no longer Available, someone has reserved or started it: coordinate with them or choose another paper. 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",
"context_md": null,
"benchmark": null,
"skill_refs": [
{
"skill_version_id": "skv_k5sivlohu1",
"requirement": "required"
}
],
"verifier_contract_id": "vct_4t6ri8zibj",
"verifier_input_bindings": [
{
"key": "card",
"content_hash": "sha256:f71e58f620f577e1d08cbd1915249fb01d40e3d2d67addb983b759242055fd71",
"size_bytes": 3630,
"media_type": "application/json",
"filename": "card.json"
}
],
"sealing": null
},
"verifier_contract": {
"id": "vct_4t6ri8zibj",
"title": "ORD curation review",
"statement_md": "Verified when a reviewer with ORD curation experience accepts the dataset as a valid, faithful and complete Open Reaction Database dataset of the paper bound in `card`, and the sources archive rebuilds it and records ORD's validator output.",
"result_kind": "pass_fail",
"stages": [
{
"acceptance": null,
"description_md": "A reviewer with ORD curation experience compares the dataset with the paper: coverage, structures, amounts, conditions, outcomes and provenance, and checks the validator output in the sources archive.",
"evidence_schema": null,
"external_system": null,
"key": "curation_review",
"kind": "review",
"review_protocol_id": "rpt_mumofu1g8r",
"rule_owner": null,
"title": "Curation review"
}
],
"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 with a README, 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.",
"max_bytes": 26214400,
"media_types": [],
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"score": null
},
"api": {
"problem": "/api/problems/prb_5sa1dgmzdx",
"revision": "/api/problems/prb_5sa1dgmzdx/revisions/1",
"mcp": "start_attempt {\"problem\":\"ord-angello-2022-suzuki-closed-loop\",\"revision\":1,\"provenance\":\"mixed\"}"
}
}