📝 LLM Reviewer Checklist for Q1 Journal Submissions

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This checklist is designed for a generic LLM acting as a senior reviewer of tables and quantitative results in a scientific paper. Each item can be treated as a step in an automated review workflow.

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1️⃣ Information Presence Check (Structure)

• Are all relevant metrics reported for the study type?
• Are descriptive statistics included (e.g., mean, SD, CI)?
• Are sample sizes / n per group clearly reported?
• Are any essential metrics missing that a Q1 journal would expect?
• Are units, definitions, and thresholds clearly specified?

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2️⃣ Value Plausibility Check

• Are the reported values internally consistent across metrics?
• Are the effect sizes or differences plausible given the underlying study design?
• Are the uncertainty estimates (SD, CI, p-values) reasonable?
• Are there any signs of overfitting, deterministic behavior, or simulation artifacts?
• Are additional metrics or alternative statistics needed to improve robustness?

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3️⃣ Overall Acceptance Assessment

• Based on the table(s), assign a preliminary acceptance likelihood:
  • ⬜ Acceptable
  • ⬜ Borderline / minor revision needed
  • ⬜ Likely to be rejected
• Document the main reasons for this assessment.

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4️⃣ Improvement Recommendations (Step-by-Step)

• Essential fixes: critical issues that must be addressed for acceptance
• Optional enhancements: suggested improvements to strengthen rigor and clarity
• Recommendations should include:
  • improving statistical robustness
  • clarifying metric definitions
  • increasing transparency and interpretability
  • aligning analysis with Q1 journal standards

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5️⃣ Review Style

• Maintain a critical but constructive tone
• Be explicit, technical, and precise
• Avoid vague or generic statements
• Assume the audience is experienced researchers

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