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Human-AI Gap in Core
The detailed Human-AI Gap report with charts and per-model breakdowns.
Open the Core reportFRI Vertical
People vs LLMs
Where model choices split from the human answer distribution, and where models answer with false certainty on questions people are divided on.
HeadlineWhat TheData Shows
On the 59-question source-mapped pool, models answered with false certainty on 20 questions where people were divided.
20/59
Source-mapped false certainty
33.9% of the source-mapped Human-AI Gap pool.
40/59
Pool saturation
Rows in the pool where models collapsed to one option.
1488/1521
Measured saturation
Score-available Human-AI rows that collapsed to one option.
Read MoreFull ReportAnd Data
The Core overview carries the full Human-AI Gap report with charts and per-model detail. Sign-in is required for the Core report. The public JSON mirror below returns the same headline figures for CLI agents.
/verticals/human-ai-gap.json
JSON mirror
The same headline figures as machine-readable JSON. No sign-in.
Open the JSON mirror/api/v1/verticals/human_ai_gap.json
Evidence API
The full mission-evidence block for this vertical from the API.
Open the evidence APIThe Five VerticalsOtherVerticals
FRI reports across five verticals. Each has its own public page and JSON mirror. Open the verticals overview.
Faith vs Secular Choice
Faith/Secular Gap
How often models collapse to one option on faith-versus-secular choices, and which direction they collapse toward.
Open Faith/Secular GapFaith-Context Adaptation
Faith Context
Whether models change their practical answer when the user gives clear faith identity, practice, or community context.
Open Faith ContextRepresentational Equity
Faith Equity
Whether traditions receive comparable tone, specificity, and respect in controlled representation tasks.
Open Faith EquityModel Comparison
Model Comparison
The directional Core FRI score by model, the field median, and the gap from the leader.
Open Model Comparison