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Primary Bias
An AI model's ungrounded confidence in an entity, formed during training and present before any retrieval; in AI search it is the largest single factor in whether a source is selected.
Primary bias is an AI model's ungrounded confidence in an entity, formed during training and present before any search or retrieval happens. It is the model's pre-judgement, baked into its weights, and in AI search it is the largest single factor in whether a source is selected.
It is slow to change because it lives in the training data, and it is measured through its effect on the Selection Rate. Full article: Primary Bias. Its post-retrieval counterpart is secondary bias, which includes grounding bias. Related: AI Visibility.
Mentioned in
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Grounding Source ≠ Citation ≠ Mention
Being a cited grounding source does not mean your brand was mentioned in the answer, and being mentioned does not mean you were cited. They are correlated but distinct events produced at different stages of the AI answer pipeline — and conflating them is the source of most AI-visibility measurement
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Primary Bias
Primary bias is what an AI model already believes about your brand before it searches: an ungrounded confidence baked into training that becomes the biggest factor in whether your content is selected in AI answers.
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Grounding Snippets
Grounding snippets are the short, extractive sentences AI systems pull from your page to build their answers: the atomic unit of AI-search visibility, where most of your page never makes the cut.