Skill UI

A comprehensive style guide and checklist for writing and refining long-form academic articles for 'Pattern Recognition and Artificial Intelligence' (PR&AI). It covers the entire publishing workflow, from mastering the structured introduction (Problem-Gap-Contribution) and writing four-element abstracts, to adhering to rigorous standards for citations (GB/T 7714), figures, and mathematical notation in AI research.

This guide teaches authors how to structure the Introduction and Discussion sections for top-tier journals with extreme word and reference constraints. It moves beyond traditional literature reviews, focusing on a 'surgical' approach: quickly establishing the research gap, clearly stating the unique contribution, and demonstrating the broad relevance of the findings to the wider field.

This skill guides researchers in transforming raw meta-analysis results (e.g., pooled effects, moderator analyses) into a genuine, high-impact theoretical contribution suitable for integrative review journals. It teaches how to interpret conflicting findings, build or refine theoretical models, clearly state scope conditions (boundary conditions), and set concrete future research agendas, ensuring the findings advance the field beyond mere statistics.

This skill guides researchers on whether a proposed research topic is suitable for a high-level synthesis journal (like Psychological Bulletin). It assesses the existing literature's depth, general academic significance, and whether the contribution is synthesizing prior findings. It determines the most appropriate synthesis methodology—such as meta-analysis, systematic review, or qualitative meta-synthesis—by comparing the nature of the pooled data.

A guide for articulating the unique theoretical advancement of a psychological review manuscript. It instructs authors on how to frame their findings using the 'before $\rightarrow$ after' structure, defining what the field can explain after the paper that it could not previously, and critically identifying the specific prior models improved upon.

This guide assists researchers in the rigorous construction of psychological theories and formal models for academic manuscripts. It provides a step-by-step methodology to move from initial intuition to an explicit, testable theoretical structure. Users learn to define core assumptions, specify underlying causal mechanisms, and formalize models using mathematical equations or precise conceptual frameworks, ensuring the derived model behavior is the central contribution.

This guide provides best practices for positioning a scholarly manuscript within the field of public administration. It instructs authors on how to elevate their niche contributions into field-wide debates, ensuring the paper speaks to both academic scholars and practicing managers. It emphasizes linking theory gaps to practical policy stakes.

This skill guides authors in transforming empirical research findings into a robust theoretical contribution for Public Administration. It emphasizes articulating clear mechanisms, defining necessary scope conditions, and providing actionable "Evidence for Practice," ensuring the work advances both academic theory and real-world policy.

This guide helps authors refine the core contribution sentence for Quantitative Economics (QE) manuscripts. It shifts the focus from complex methodology (machinery) to the clear, quantitative economic answer (the payoff). Learn to structure claims by linking a clear economic question, a measured quantity (estimate, counterfactual), and a broader policy lesson, while explicitly stating scope and uncertainty to meet high academic standards.

A comprehensive guide for authors to pinpoint the unique quantitative contribution (the 'delta') of their manuscript. It teaches how to articulate the specific gap closed relative to prior empirical, structural, and methodological work, ensuring the paper is correctly positioned for target journals like QE, distinguishing it from related fields.

This router guides authors through the complex publication lifecycle for Quantitative Economics (QE) submissions. It diagnoses current bottlenecks—whether in topic framing, data analysis, contribution clarity, or writing style—and directs the user to the precise specialized skill needed at that stage, ensuring a structured path from initial concept to final submission or rebuttal.

This skill polishes scholarly prose, abstracts, and introductions to align with the narrative-driven, ambitious style of the Quarterly Journal of Economics (QJE). It focuses on making the core research contribution immediately legible to a general-interest, non-specialist reader, ensuring the big idea lands fast, even in long-form empirical papers. The skill guides users on structuring the 'introduction arc,' stating findings with concrete numbers, and minimizing technical jargon.