{
  "problem": {
    "id": "prb_dlptpr6sxh",
    "slug": "ord-sagmeister-2022-multistep-flow-optimization",
    "title": "Autonomous Multi-Step and Multi-Objective Optimization Facilitated by Real-Time Process Analytics",
    "summary": "Curate this paper's reaction data into a validated Open Reaction Database dataset. Advanced Science 2022, DOI 10.1002/advs.202105547. Automated flow. Source data: data that must be requested from the authors.",
    "structure": "SOLVE"
  },
  "revision": {
    "sealing": null,
    "id": "prv_5t868l1sir",
    "problem_id": "prb_dlptpr6sxh",
    "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:** Autonomous Multi-Step and Multi-Objective Optimization Facilitated by Real-Time Process Analytics\n- **Authors:** Peter Sagmeister, Florian F. Ort, Clemens E. Jusner et al.\n- **Published:** Advanced Science, 2022-02-01\n- **DOI:** [10.1002/advs.202105547](https://doi.org/10.1002/advs.202105547)\n- **ORD wishlist card:** [open on GitHub](https://github.com/orgs/open-reaction-database/projects/11?pane=issue&itemId=126569972)\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 (automated flow): 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\nAutonomous multi-step, multi-objective self-optimization in continuous flow, using inline benchtop NMR and FTIR with chemometric models (indirect hard modeling) as real-time process analytics. Per the Data Availability Statement, the underlying data are available from the corresponding author on request. No public data deposit was found. The SI (PDF) may contain partial tables of optimization experiments but has not been inspected. Curation is blocked until the experimental data are obtained. The article text and SI can then supply conditions: flow rates, residence times, temperatures, equivalents, and outcomes quantified by NMR/IR models. Structures are small molecules, so SMILES must be written by the curator.\n\nKnown locations:\n\n- [https://europepmc.org/article/PMC/PMC8981902](https://europepmc.org/article/PMC/PMC8981902): Open full text (Europe PMC XML fetched). The data statement says 'available from the corresponding author upon reasonable request'. SI file ADVS-9-2105547-s001.pdf is listed but was not retrievable (403). (license: CC-BY-4.0 (article))\n- [https://doi.org/10.1002/advs.202105547](https://doi.org/10.1002/advs.202105547): Publisher landing (Wiley, Advanced Science, open access) (license: CC-BY-4.0 (article; SI and data terms not stated))\n\n## Pitfalls\n\nMulti-step telescoped flow with outcomes quantified by chemometric models on inline NMR/FTIR rather than chromatography, so analysis provenance must be described. Self-optimization iterations are sequential steady states. Multi-objective outcomes (yield, throughput, etc.) may need custom measurements.\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:c2c17f5df7589868a24a0e8cbf2db90bca8486024c1594b64788fc9a4fd0d390",
        "size_bytes": 2651,
        "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"
  }
}