Quantitative Claims

Open Quantitative Claims ToolBrowse numbers and statistics extracted from all content

How It Works

The Quantitative Claims tool scans all MDX content for numbers, percentages, dollar amounts, and other quantitative data that could be extracted as standalone insights.

Patterns Detected

Type	Examples	Description
Percentages	40%, 30-50%	Success rates, probabilities, coverage
Dollar Amounts	$1B, $10 million	Research funding, market sizes, costs
People Counts	500 researchers	Team sizes, community estimates
Timelines	by 2030, in 5 years	Predictions, forecasts
Multipliers	10x, 3-fold	Performance gains, risk increases
Probabilities	20% probability	Risk estimates, likelihood
Large Numbers	100 billion	Scale metrics

Notable Claims

Claims are marked as "Notable" when their surrounding context contains importance indicators like:

catastrophic, existential, critical
surprising, unexpected, contrary
only, merely, just (indicating scarcity)
most, majority (indicating prevalence)
unprecedented, first

Generating the Data

The claims data is generated by running:

cd apps/longterm
node scripts/find-quantitative-claims.mjs

This scans all MDX files and outputs to src/data/generated/quantitative-claims.json.

Re-run this script periodically to capture new content.

Using the Tool

Filter by type to focus on specific claim types (percentages, dollars, etc.)
Toggle "Only notable" to see claims with importance indicators
Search for specific topics or numbers
Click through to source pages to verify context
Extract as insight if the claim is surprising, important, and well-sourced

Tips for Good Quantitative Insights

Good candidates:

Specific percentages with clear methodology
Dollar amounts that reveal priorities
Timeline predictions from credible sources
Multipliers that show scale of change

Poor candidates:

Round numbers without sources (e.g., "about 50%")
Dates that are just timestamps
Numbers in code examples or technical specs
Statistics already well-known in the field