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reading correctly credits the four listed authors with introducing CASEL. Results are framed as findings reported by the paper, not as established facts or Escape Meridian's view.","excerpt":"Authors:Yanyan Zhang, Fei Shen, Ting Yan, Hao Zhang"},{"dimension":"summary","status":"uncertain","explanation":"The reading is faithful, but its opening never says CASEL is for AI language-model agents that call software tools. A newcomer meets 'proposed tool call' and 'runtime allocation policy' with no plain context. The AI-agent framing appears only later and indirectly. Smallest repair: in the first sentence, identify CASEL as a safeguard layer for AI language agents whose tool calls can change external systems. Lesser points: 'calibrated' and 'state-dependent' are dropped from the factor list, and the summary omits the headline magnitudes (14.75 to 7.02 percent), though the claims keep them.","excerpt":"Tool-using language agents increasingly modify external systems, yet most runtime safeguards allocate scrutiny by generic uncertainty scores or coarse mutation heuristics."},{"dimension":"date","status":"pass","explanation":"originalPublished is 2026-10-27, which matches the v1 submission date on arXiv. It is not the later feed date of 2026-10-29.","excerpt":"[Submitted on 27 Oct 2026]"},{"dimension":"support","status":"pass","explanation":"Each claim matches the abstract: the comparison with the uncertainty-ranked gate, the probability-times-consequence gate sending 45 percent more actions to human approval, the reversibility ablation, and the worse trajectory-level risk budget. The simulation-only caveat is kept prominently. 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