+
Methodological rigor visibly upgraded: PRISMA-ScR diagram, explicit Methods/Results split, transparent Boolean search log in Table 1 and Appendix A, and study-type coding in Appendix D answer multiple reviewers simultaneously.
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The Verification-Value Paradox is now actionable through Table 7's decision criteria and the task-stakes classification in Table 6, directly resolving a criticism shared by Reviews 2, 5, and 7.
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AI-type distinction (LLM / narrow ML / XAI) is properly integrated as a cross-cutting modifier in Section 3.5 and Table 4, rather than added cosmetically.
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Use case is substantially sharpened with specific tools (Harvey, Lexis+ AI, CoCounsel) and an explicit junior/senior role distinction that turns abstract calibration into operational guidance.
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Framework figure (Figure 2) now correctly conveys interconnection and bidirectionality with a central Calibrated Trust node, replacing the prior linear top-to-bottom diagram criticised by Reviews 1, 6, and 9.
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Cross-domain Table 5 provides concrete medicine and architecture parallels, and the transferability claim is appropriately softened to "potential transferability."
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Corpus expanded from 21 to 50 sources, addressing concerns about evidence-base thinness raised by Review 9.
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Empirical contradictions (Naiseh vs. Senoner; Bansal et al.) are now explicitly surfaced and resolved through user-expertise and cognitive-load moderators rather than glossed over.
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Concrete, testable hypotheses in Section 6 replace the generic "future work" prose of the original, addressing Reviews 2 and 4.
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Balance between overtrust and undertrust is restored through integration of algorithm appreciation (Logg 2019) and explicit treatment of senior-lawyer undertrust as costly miscalibration in Section 4.
−
The domain-agnostic claim is better supported but still rests on illustrative tables rather than a second, fully developed worked use case (e.g., a clinical or architectural drafting scenario walked through all four dimensions).
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Demographic, jurisdictional, and cultural variation remains acknowledged-only in Section 6; no synthesis is performed across the empirical studies that were included, leaving Review 2 and Review 4's concern only partially addressed.
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The corpus skews heavily to policy/institutional sources (20/50, i.e., 40%) versus 15 empirical studies; the evidentiary weight of the framework still leans on guidance documents.
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Several 2026 references (Liebherr et al. 2026; Pal et al. 2026 with anomalous DOI; Chaos Group 2026; VirtualSpaces 2026; Chang 2026) warrant verification — given the paper's own emphasis on hallucinated citations, source authenticity is a meta-credibility concern.
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UI/UX factors in Intrinsic Trustworthiness (Review 5's point about warnings, highlights, indicators) are mentioned only briefly via Kim et al. and Küper et al.; not developed as a sub-theme.
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The Discussion (Section 5) does not explicitly loop back to the four sub-questions posed in the Introduction, leaving the closure of the original research framing implicit.