{
"problem": {
"id": "prb_5f5ty4g03f",
"slug": "ord-soleimany-2024-multiattribute-process-optimization",
"title": "Doing More with Less, On Time and In Full: An Intelligent Multiattribute Process Optimization Platform",
"structure": "SOLVE",
"status": "open",
"campaign": "open-reaction-database-wishlist",
"summary": "Curate this paper's reaction data into a validated Open Reaction Database dataset. OPRD 2024, DOI 10.1021/acs.oprd.3c00392. Source data: data that must be requested from the authors."
},
"revision": {
"id": "prv_alnex8j011",
"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:** Doing More with Less, On Time and In Full: An Intelligent Multiattribute Process Optimization Platform\n- **Authors:** Reihaneh Soleimany, Wenyao Zhang, Jee Seong Kwak et al.\n- **Published:** OPRD, 2024-02-26\n- **DOI:** [10.1021/acs.oprd.3c00392](https://doi.org/10.1021/acs.oprd.3c00392)\n- **ORD wishlist card:** [open on GitHub](https://github.com/orgs/open-reaction-database/projects/11?pane=issue&itemId=126570026)\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: 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\nPaper: Soleimany et al., Org. Process Res. Dev. (published online 2024), doi:10.1021/acs.oprd.3c00392 (closed access). It describes an intelligent multiattribute process-optimization platform. The underlying experiment-level reaction data may not be in the SI; the curator needs to confirm whether per-experiment conditions and outcomes are tabulated. If they are not, the data must come from the authors. Optimization campaigns often record several responses per experiment (yield, impurity levels and so on), and each should become a separate ProductMeasurement.\n\nKnown locations:\n\n- [https://doi.org/10.1021/acs.oprd.3c00392](https://doi.org/10.1021/acs.oprd.3c00392): OPRD article and Supporting Information; contents not verified (license: ACS publisher terms (closed article))\n\n## Pitfalls\n\nAlgorithm-driven optimization campaigns may include sequential or iterative experiments, possibly in flow, where time ordering and multiple responses per run matter. Multi-objective outcomes (yield, purity, impurities) have to be mapped onto ORD measurement types.\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:fac2dc2eba055d1b5bcedba2183abc509dab74df119934a7f984abd09a1053e0",
"size_bytes": 2007,
"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": [],
"role": "sources"
}
]
},
"score": null
},
"api": {
"problem": "/api/problems/prb_5f5ty4g03f",
"revision": "/api/problems/prb_5f5ty4g03f/revisions/1",
"mcp": "start_attempt {\"problem\":\"ord-soleimany-2024-multiattribute-process-optimization\",\"revision\":1,\"provenance\":\"mixed\"}"
}
}