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research-control

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🗂️ AI & Agents · View mindmap

Research Control

Research Control refers to the granular control capabilities provided to users within the ChatGPT Deep Research feature. This functionality allows users to specify and manage which sources are utilized during the research process, enabling more customized and targeted information gathering according to individual needs and preferences. By offering control over source selection, Research Control helps users tailor the research output to align with their specific requirements and quality standards.

Functionality

The ChatGPT Deep Research update integrates research source management directly into the user interface, allowing users to configure parameters that influence which sources the system prioritizes or excludes. This level of control enables researchers, analysts, and information seekers to focus their queries on preferred domains, publication types, or credibility levels. Users can adjust these settings to balance comprehensiveness with source quality according to their particular use case.

Applications

Research Control is particularly valuable in contexts where source reliability is critical, such as academic research, professional analysis, or domain-specific investigations. By enabling users to define their source parameters upfront, the feature reduces the need for post-processing of results and helps ensure that generated research aligns with methodological requirements or institutional standards. This makes the deep research capability more adaptable to specialized workflows and quality expectations.

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