{
  "problem": {
    "id": "prb_nebjate0as",
    "slug": "ord-jiang-2025-open-hts-robotic-screening",
    "title": "Exploring New Reactions with an Accessible High-throughput Screening (Open-HTS) Chemical Robotic System",
    "summary": "Curate this paper's reaction data into a validated Open Reaction Database dataset. OPRD 2025, DOI 10.1021/acs.oprd.5c00027. About 3,920 reactions · HTE photo flow. ORD wishlist priority High, difficulty Hard. Source data: plate images or heatmaps.",
    "structure": "SOLVE"
  },
  "revision": {
    "sealing": null,
    "id": "prv_53qgwifdnt",
    "problem_id": "prb_nebjate0as",
    "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:** Exploring New Reactions with an Accessible High-throughput Screening (Open-HTS) Chemical Robotic System\n- **Authors:** Heming Jiang, Ying Chen, Meirong Huang et al.\n- **Published:** OPRD, 2025-05-28\n- **DOI:** [10.1021/acs.oprd.5c00027](https://doi.org/10.1021/acs.oprd.5c00027)\n- **ORD wishlist card:** [open on GitHub](https://github.com/orgs/open-reaction-database/projects/11?pane=issue&itemId=127178740)\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 3,920 reactions; HTE photo 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\nOpen-HTS accessible robotic high-throughput screening, including photo/flow reactions (Peking University / Shenzhen Bay Laboratory), OPRD 2025, DOI 10.1021/acs.oprd.5c00027 (closed article). Results for about 3920 reactions appear in the paper as an image grid, with 83 hits, and the primary readout is qualitative (whether the product ion was detected by MS). The SI on ACS figshare is a 17 MB PDF plus two videos. No machine-readable data file or public code repository was found. A spreadsheet of the screen (components per well and detection result) is needed before curation.\n\nKnown locations:\n\n- [https://doi.org/10.1021/acs.oprd.5c00027](https://doi.org/10.1021/acs.oprd.5c00027): Article landing page (OPRD) with the result image grid (license: closed (OpenAlex); ACS TDM policy per Crossref)\n- [https://acs.figshare.com/articles/journal_contribution/29175858](https://acs.figshare.com/articles/journal_contribution/29175858): SI PDF op5c00027_si_001.pdf (17.4 MB). Listing only, not downloaded. (license: CC BY-NC 4.0 (figshare label))\n- [https://acs.figshare.com/articles/media/29175861](https://acs.figshare.com/articles/media/29175861): SI videos op5c00027_si_002.mp4 and si_003.mp4 (record 29175864) of the robotic system. Not reaction data. (license: CC BY-NC 4.0 (figshare label))\n\n## Pitfalls\n\nOutcomes are qualitative (product ion detected yes or no), with no yields. Products are mostly not isolated or characterized. Reading about 3920 wells from an image is error-prone, and component SMILES must be generated.\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:c387e442d6dccbb2c1e70b75882b0b7581911e5616b2f8e2487b1cd1dbb49f9e",
        "size_bytes": 2478,
        "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"
  }
}