1. The Concept, Plainly
When an AI system — ChatGPT, Claude, Gemini — answers a question and names a source, that source has been cited. Research shows that AI systems are more likely to cite content that contains verifiable claims: statements tied to a specific number, a named source, or a dated finding. The ratio of verifiable claims to total words in a piece of content is called statistical density. Higher density correlates with higher citation rates.
2. Why This Matters Right Now
If you publish content and want AI systems to surface it when someone asks a relevant question, the writing patterns that help with that goal are measurable. Statistical density is one of those patterns. You do not need to guess whether your content has it — you can measure it right now using the same AI tools you already have access to. The mechanism behind why AI systems weight this pattern is worth understanding before you measure, because once you see it, the number you get back from your measurement will make sense.
3. The Mechanism
AI systems learn to answer questions by processing large amounts of text and identifying which content reliably provides accurate information. Over time, they develop a pattern: content that contains specific, checkable claims — numbers tied to measurements, named studies, dated findings, direct quotations — is more likely to be accurate than content that contains only general assertions.
This is not a rule someone programmed in. It is a learned association. Content with verifiable claims has, in practice, been more reliably correct. So AI systems have developed sensitivity to the signals that verifiable claims leave in text: a year, a percentage, a named author, a specific sample size.
A 2024 study by Aggarwal et al., published at KDD (one of the largest data mining research conferences), quantified one part of this pattern directly. Including statistics in content was associated with approximately a 31% increase in the probability that an AI system would explicitly name the source when answering a relevant question. Adding an explicit source reference alongside the statistic compounded this further — approximately another 30% increase on top.
"Citation probability" here means the AI names the source explicitly, as in "According to Aggarwal et al. 2024..." — not just that it uses the information without attribution. That distinction matters: absorption (AI uses your information silently) and citation (AI names you) are separate outcomes.
We tested this association against an internal corpus of 36 articles. The result tracked with the external research. Articles in the lowest statistical density quartile — those with 3.7 to 12.5 verifiable claims per 1,000 words — were cited in 33% of queries. Articles in the highest quartile — 42.8 or more verifiable claims per 1,000 words — were cited in 89% of queries. The Spearman correlation between density and citation rate across the corpus was 0.47. That is a moderately strong positive association. All of these findings are correlational, not causal — the density pattern predicts citation, but does not guarantee it.
One more finding worth holding: content written at Flesch-Kincaid grade 8–10 shows meaningfully higher AI extraction rates than content at grade 12 or above. Grade 8–10 is roughly the reading level of a clear newspaper article. Grade 12 is the reading level of a dense academic paragraph. AI systems extract more reliably from content that is written clearly. Statistical density and readability work together.
The practical picture is this: a piece of content with specific, sourced, dated claims written at a clear reading level is far more likely to be named by an AI than a piece of content with vague, general assertions written in dense prose — even if both are on the same topic and both are accurate.
4. Try It Now
You can measure the statistical density of your own content in under five minutes using a tool you already have.
Paste this prompt:
"Read the following passage and identify every verifiable claim — defined as any sentence containing a specific number tied to a measurement, a named source, a date-stamped finding, or a direct quotation. List each verifiable claim you find. Then count the total number of verifiable claims and divide by the total word count of the passage. State the ratio as verifiable claims per 1,000 words.
[Paste your content here]"
What to look for in the output: The AI will separate sentences it can verify (specific numbers, named sources, dated findings) from sentences it cannot (general assertions like "studies show," "research suggests," "many experts agree"). The gap between what you thought was substantiated and what the AI flags as verifiable is your current density gap. A ratio below 12.5 verifiable claims per 1,000 words puts you in the lowest citation-rate quartile; above 42.8 puts you in the highest.
Pick a piece of your own content — a blog post, an article, a product page. Paste a section of 200–400 words into the prompt. The ratio the AI returns is your current statistical density.
5. The One Thing to Remember
AI systems cite content that contains claims they can check — specific numbers, named sources, dated findings. The ratio of those claims to your total word count is statistical density, and it is measurable right now.
6. Go Deeper
The Field Notes post on the Aggarwal et al. 2024 study covers the full methodology, the confidence-level caveats, and what the corpus data reveals about density thresholds: Why Statistics in Your Content Increase AI Citation Probability.
Measure your statistical density now.
The Evidence Density Score applies the Aggarwal et al. findings directly — measuring statistics, quotations, readability, and structure in a single 0–100 score. Peer-reviewed source. No signup.