What Is a Consensus Score — and How Do You Read It?
ConvergePanel's consensus score (0–100) measures how much five AI models agree on a verdict. Learn how to read it and what thresholds mean.
Who this is for
AI-curious professionals — Anyone using ConvergePanel or evaluating multi-model AI verification tools
The problem
When five AI models evaluate the same claim, they don't always agree. One might rate it accurate; another partially accurate; a third unverifiable. How do you turn that into one actionable number? And once you have a number, what does it mean for how you should act on the result?
How ConvergePanel helps
ConvergePanel's consensus score is a 0–100 number that quantifies how much the panel's models agree on a verdict. A score of 90+ means strong convergence — the models are aligned. A score of 50 means significant disagreement — treat the claim with skepticism. A score below 40 means the claim is genuinely contested or lacks verifiable grounding. The score isn't just a summary — it's a signal about where human judgment needs to engage most.
How it works
- 1Submit a claim or research question to ConvergePanel
- 2Each model independently rates the claim and provides evidence
- 3ConvergePanel calculates the consensus score based on verdict agreement and evidence alignment
- 4Read the score: 80–100 is high confidence, 60–79 is moderate with notable disagreements, below 60 warrants additional scrutiny
- 5Use the per-model breakdown to understand what's driving disagreement in low-consensus results
Use cases
- Understanding whether an AI-verified claim is safe to act on
- Setting team governance thresholds: 'flag anything below 70 for review'
- Explaining to stakeholders what level of confidence exists in an AI-assisted finding
- Prioritizing manual verification resources toward the claims with the lowest consensus scores
Frequently asked questions
What does a consensus score of 0–100 mean?
The consensus score measures how much the five AI models in ConvergePanel's panel agree on a verdict. A score of 80–100 indicates strong agreement — most models rate the claim similarly. A score of 50–79 indicates notable disagreement worth investigating. Below 50 means significant splits or that the claim is largely unverifiable by the models.
What consensus score threshold should I use for governance policies?
ConvergePanel lets you set your own thresholds based on your risk tolerance. A common starting point is 75: claims above 75 pass automatically, claims between 50–75 get flagged for review, and claims below 50 require explicit human sign-off. Higher-stakes contexts often use 80 as the pass threshold.
Can a claim have a high consensus score and still be wrong?
Yes. A high consensus score means the AI models agree — not that they're correct. All five models share training data biases, and can converge on an inaccuracy that's widely represented in their training data. The consensus score is a reliability signal, not a guarantee. For high-stakes claims, it should inform — not replace — human judgment and primary-source verification.
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ConvergePanel provides AI-assisted verification for informational purposes only. Not forensic analysis. Not legal evidence.
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