{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T01:24:09Z","timestamp":1772241849812,"version":"3.50.1"},"reference-count":211,"publisher":"IOP Publishing","issue":"3","license":[{"start":{"date-parts":[[2025,7,17]],"date-time":"2025-07-17T00:00:00Z","timestamp":1752710400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,7,17]],"date-time":"2025-07-17T00:00:00Z","timestamp":1752710400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"funder":[{"name":"Carnegie Bosch Institute"}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["Mach. Learn.: Sci. 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My discussion concludes with an examination of how the harm associated with foundation models can be minimized and further poses a set of serious lingering questions for chemical practitioners and scientific ethicists.<\/jats:p>","DOI":"10.1088\/2632-2153\/adec3c","type":"journal-article","created":{"date-parts":[[2025,7,4]],"date-time":"2025-07-04T18:54:46Z","timestamp":1751655286000},"page":"035007","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Considering the ethics of large machine learning models in the chemical sciences"],"prefix":"10.1088","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1554-197X","authenticated-orcid":true,"given":"Evan Walter Clark","family":"Spotte-Smith","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"266","published-online":{"date-parts":[[2025,7,17]]},"reference":[{"key":"mlstadec3cbib1","first-page":"pp 1877","article-title":"Language models are few-shot learners","volume":"vol 33","author":"Brown","year":"2020"},{"key":"mlstadec3cbib2","article-title":"DeepSeek-R1: incentivizing reasoning capability in LLMs via reinforcement learning","author":"(DeepSeek-AI)","year":"2025"},{"key":"mlstadec3cbib3","article-title":"Learning transferable visual models from natural language supervision","author":"Radford","year":"2021"},{"key":"mlstadec3cbib4","first-page":"pp 10684","article-title":"High-resolution image synthesis with latent diffusion models","author":"Rombach","year":"2022"},{"key":"mlstadec3cbib5","article-title":"Visual instruction tuning","author":"Liu","year":"2023"},{"key":"mlstadec3cbib6","doi-asserted-by":"publisher","first-page":"368","DOI":"10.1039\/D2DD00087C","article-title":"Assessment of chemistry knowledge in large language models that generate code","volume":"2","author":"White","year":"2023","journal-title":"Digit. 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