Unverified50% confidenceSolutionExact time
The decision model itself only outputs probabilities, and the automation threshold is determined by the application layer; for example, it can be set so that cases with a probability above 0.9 are handled automatically and otherwise routed to human review.
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50%
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Long-term
Relevance
10/21/2026
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Related Claims
UnverifiedThe probabilistic gate uses a decision-specific model to convert tool calls into approval probabilities, and then a three-way gate decides approval, rejection, or delay.80% similarUnverifiedGenerative models cannot produce calibrated class probabilities, whereas decision models can output a calibrated probability distribution for threshold-based judgment.76% similarUnverifiedThe decision model evaluates state against bounded criteria and returns a decision score without producing an open-ended token stream, and runs in milliseconds.76% similarVerifiedThe path reasoning of AI models is based on statistical probability rather than deterministic logic; their behavior is determined by probability distributions, and a residual uncertainty exists in every execution.75% similarVerifiedThe probability figures provided by guided generative models are essentially 'well-constrained inferences' rather than directly verifiable truths.74% similar
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