Selected Ion Monitoring Using Low-Cost Mass Spectrum Detectors Provides a Rapid, General, and Accurate Method for Enantiomeric Excess Determination in High-Throughput Experimentation
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"slug": "ord-korch-2022-sim-ms-ee-hte",
"title": "Selected Ion Monitoring Using Low-Cost Mass Spectrum Detectors Provides a Rapid, General, and Accurate Method for Enantiomeric Excess Determination in High-Throughput Experimentation",
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"summary": "Curate this paper's reaction data into a validated Open Reaction Database dataset. ACS Catalysis 2022, DOI 10.1021/acscatal.2c01628. About 96 reactions · HTE. ORD wishlist priority Medium, difficulty Hard. Source data: tables in the Supporting Information PDF."
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"created_at": "2026-10-14T19:42:49Z",
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"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:** Selected Ion Monitoring Using Low-Cost Mass Spectrum Detectors Provides a Rapid, General, and Accurate Method for Enantiomeric Excess Determination in High-Throughput Experimentation\n- **Authors:** Katerina M. Korch, Jacob C. Hayes, Raphael S. Kim et al.\n- **Published:** ACS Catalysis, 2022-05-23\n- **DOI:** [10.1021/acscatal.2c01628](https://doi.org/10.1021/acscatal.2c01628)\n- **ORD wishlist card:** [open on GitHub](https://github.com/orgs/open-reaction-database/projects/11?pane=issue&itemId=126844397)\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 96 reactions; HTE): 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\nSource: Korch et al., ACS Catal. 2022, doi:10.1021/acscatal.2c01628; NIH author manuscript and SI on PMC (PMC9894240). The paper uses selected ion monitoring with a low-cost MS detector to determine enantiomeric excess in HTE. About 96 reactions are tabulated across four tables in the Supporting Information PDF. Transcribe the reaction conditions and ee (and yield where given) per well. Assign stereo-defined SMILES for the chiral catalysts/ligands and products. Record the analytical method (SIM-MS, and UV/vis where given for comparison). The authors may hold a machine-readable CSV of these tables, but the public SI is enough. The SI is not openly licensed. Cite it, but do not redistribute it.\n\nKnown locations:\n\n- [https://doi.org/10.1021/acscatal.2c01628](https://doi.org/10.1021/acscatal.2c01628): ACS Catalysis article landing page and ACS-hosted SI (experimental details, tabulated data, LC traces) (license: ACS publisher terms)\n- [https://pmc.ncbi.nlm.nih.gov/articles/PMC9894240/](https://pmc.ncbi.nlm.nih.gov/articles/PMC9894240/): PMC NIH author manuscript (NIHMS1865591) (license: NIH public access author manuscript (not an open license))\n- [https://pmc.ncbi.nlm.nih.gov/articles/instance/9894240/bin/NIHMS1865591-supplement-supporting_information.pdf](https://pmc.ncbi.nlm.nih.gov/articles/instance/9894240/bin/NIHMS1865591-supplement-supporting_information.pdf): Supporting Information PDF (13.3 MB; listed on PMC, not downloaded) with the four data tables (license: not openly licensed (ACS SI via NIH public access))\n\n## Pitfalls\n\nThe primary outcome is ee, possibly reported by both SIM-MS and UV for the same wells, so the ORD record should keep the two analyses distinct. The four tables may cover different reactions or conditions, which could mean multiple templates. Chiral catalysts need correct stereochemistry. The paper is methods-focused, so some rows may be calibration or validation samples rather than reactions.\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",
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