Developing Best Practices for Large Language Models in Environmental Science
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| フィールド | 値 |
|---|---|
| 作成者 | Charlotte H. Chang |
| 最終更新 | 4月 23, 2026, 20:05 (UTC) |
| Published | 4月 7, 2026, 22:25 (UTC) |
| Citation | Charlotte H. Chang 2025. Developing Best Practices for Large Language Models in Environmental Science. CyVerse Data Commons. |
| 説明 | This initiative develops ethical guidelines and best practices for using AI-powered text analysis in environmental research synthesis and policy evaluation. The team creates undergraduate-accessible tools for analyzing conservation literature while leveraging NSF computing resources, advancing environmental science through responsible AI implementation. |
| PublicationYear | 2025 |
| Publisher | CyVerse Data Commons |
| Rights | This material is based upon work supported by the National Science Foundation under grant #2153040, the NSF ACCESS-CI program, which is supported by National Science Foundation grants #2138259, #2138286, #2138307, #2137603, and #2138296. This work used Jetstream2 at Indiana University through allocation BIO220085. CyVerse is based upon work supported by the NSF under Grant Nos. DBI-0735191, DBI-1265383, and DBI-1743442. |
| Subject | large language models, environmental science, AI ethics, evidence synthesis, policy analysis, computational text analysis |
| de_created_date | 2025-06-06T16:18:23Z |
| de_modified_date | 2026-04-23T19:45:48Z |