…we believe the current framing of this issue as "manipulation" and "cheating" misses a crucial opportunity to address deeper structural challenges facing academic publishing today. Rather than focusing solely on exposing problematic behavior, we propose a more constructive path forward that acknowledges the complex realities of AI integration in research workflows while strengthening the ethical foundations of peer review.

Every academic knows the feeling: waiting months for mediocre feedback while reviewers juggle impossible workloads. Here's how ReviewerZero's purpose-built AI delivers structured critique, replicability predictions, and journal recommendations.

This system implements a specialized multiagent architecture comprising five expert agents, each focusing on a distinct aspect of empirical research evaluation:

Theoretical Framing & Hypothesis Development Specialist - Evaluates theoretical grounding and hypothesis development
Empirical Identification & Methods Specialist - Assesses causal identification strategies and econometric rigor
Conceptual Clarity & Presentation Specialist - Ensures readability and presentation quality
Economic Significance & External Validity Specialist - Analyzes practical implications and generalizability
Paper Structure & Presentation Specialist - Verifies adherence to empirical research conventions

An Editor Agent synthesizes feedback from all specialists into a coherent, actionable review letter.

The Nature headline stopped me cold: "AI is transforming peer review — and many scientists are worried." Published just months ago, the article revealed that artificial intelligence software is "increasingly involved in reviewing papers, provoking interest and unease." What appeared as an efficiency breakthrough felt like witnessing the automation of centuries-old violence. Major publishers like AIP Publishing are piloting AI tools for peer review, while others explore "various potential use cases for AI to strengthen peer review." The transformation is already happening.

The landscape of artificial intelligence (AI) usage in scholarship and publishing is evolving. The editorial and management team of CFS/RCÉA acknowledges that AI tools can offer value in many scholarly processes, including ideation and concept refinement, data analysis, image/figure/table creation, audio/video production, linguistic translation, language/grammar correction, and identifying subject-specific resources. Nonetheless, AI tools also generate errors and falsehoods, can compromise the rights and licenses of authors and creators, and have themselves been created within historical biases, privileges, and prejudices. The environmental impact of the use of AI, including water and energy consumption, is also of significant ecological concern. Within this context, CFS/RCÉA accepts that AI tools may be used in the creation of material submitted to the journal, under the following conditions:

- The human authors whose names are attached to the submission must have played the primary role in the conception and construction of the content.

- A disclosure statement on the use of any AI tool(s) must be provided at time of submission.

This policy covers content submitted for publication as well as texts submitted by peer reviewers.