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The MOSDEF Survey: Direct Observational Constraints on the Ionizing Photon Production Efficiency, $\xi_ion$, at z~2

, , , , , , , , , , , , , and . (2017)cite arxiv:1711.00013Comment: 14 pages, 8 figures, 1 table, submitted to ApJ.

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Entangled Preferences: The History and Risks of Reinforcement Learning and Human Feedback., , and . CoRR, (2023)Reward Reports for Reinforcement Learning., , , , and . CoRR, (2022)RewardBench: Evaluating Reward Models for Language Modeling., , , , , , , , , and 2 other author(s). CoRR, (2024)AI Development for the Public Interest: From Abstraction Traps to Sociotechnical Risks., , , , and . CoRR, (2021)Choices, Risks, and Reward Reports: Charting Public Policy for Reinforcement Learning Systems., , , and . CoRR, (2022)The MOSDEF Survey: Direct Observational Constraints on the Ionizing Photon Production Efficiency, $\xi_ion$, at z~2, , , , , , , , , and 4 other author(s). (2017)cite arxiv:1711.00013Comment: 14 pages, 8 figures, 1 table, submitted to ApJ.The MOSDEF survey: a stellar mass-SFR-metallicity relation exists at $z\sim2.3$, , , , , , , , , and 8 other author(s). (2017)cite arxiv:1711.00224Comment: 18 pages, 7 figures, submitted to ApJ.AI Procurement Checklists: Revisiting Implementation in the Age of AI Governance., , , and . CoRR, (2024)Reward Reports for Reinforcement Learning., , , , , and . AIES, page 84-130. ACM, (2023)AI Development for the Public Interest: From Abstraction Traps to Sociotechnical Risks., , , , and . ISTAS, page 72-79. IEEE, (2020)