The document states that safety evaluation results described across system cards were conducted in an offline setting unless specifically noted otherwise, meaning they do not reflect live or production deployment conditions.
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This disclosure establishes that the safety evaluation results described in the system card are based on offline testing rather than production deployment conditions, which is a material methodological limitation for compliance teams assessing the real-world applicability of the stated safety posture.
The document states that evaluation results reflect offline testing conditions, which means the described safety performance has not been fully validated under live deployment scenarios. API users and deployers should account for this methodological scope when assessing the system card's safety disclosures.
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See how other platforms handle Offline Evaluation Scope Disclosure and similar clauses.
Compare across platforms →"Except where noted, the results in system cards describe evaluations we ran in an offline setting.Excerpt from OpenAI's GPT-5.5 System Card
(1) REGULATORY LANDSCAPE: The offline evaluation disclosure may engage with EU AI Act post-market monitoring obligations, which require ongoing safety assessment under real-world deployment conditions.
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This disclosure establishes that the safety evaluation results described in the system card are based on offline testing rather than production deployment conditions, which is a material methodological limitation for compliance teams assessing the real-world applicability of the stated safety posture.
The document states that evaluation results reflect offline testing conditions, which means the described safety performance has not been fully validated under live deployment scenarios. API users and deployers should account for this methodological scope when assessing the system card's safety disclosures.
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