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Cross-Model Confidence in the MCL Framework: Calibrated Uncertainty for Selective Judgment
A single model answers a question and, asked, reports a confidence about its own answer. That signal is introspective: nothing outside the model checks it, and a wrong answer can be a confident one. We study an alternative built on the Meta-Coordination Layer (MCL) framework: a collabor
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