Skill UI

A structured guide on translating behavioral or game-theoretic arguments into pre-specified, quantitative, and testable hypotheses for Experimental Economics (ExpEcon) manuscripts. This methodology emphasizes moving beyond informal intuition by defining the experimental game, deriving benchmark predictions, layering competing behavioral accounts, and generating comparative-statics hypotheses that treatments must adjudicate. It is essential for manuscripts aiming to robustly test theory through design.

This router guides researchers through the systematic process of preparing a manuscript for Experimental Economics (ExpEcon), the ESA's flagship journal. It identifies the correct specialized skills (e.g., theory modeling, robustness checks, referee strategy, rebuttal) needed at each stage, ensuring adherence to methodological rigor, including incentive compatibility and the no-deception norm. It is designed to help teams structure their research from initial design to final submission.

Provides rigorous guidance and structure for statistical analysis in Field Crops Research (FCR). Focuses on implementing linear mixed models that respect complex experimental designs (e.g., split-plot, block, environment). Essential for proper G×E analysis, robust means separation, and accurate evaluation of crop models, ensuring results are methodologically sound and actionable.

Provides essential guidelines for designing rigorous, generalizable field experiments in crop research. Covers multi-environment trials (MET), proper randomization, blocking strategies, split-plot designs, and Genotype-by-Environment (G×E) analysis. Use this tool when planning or defending the scientific rigor of an agricultural manuscript.

A comprehensive guide to assessing manuscript suitability for 'Financial Regulation Research.' It outlines the journal's scope (systemic risk, macroprudential policy, financial technology), required academic structure, acceptable methodologies (DID, VAR, etc.), and common pitfalls to avoid. Use this tool to refine your paper's narrative and ensure alignment with niche academic standards.

This guide outlines the rigorous methodological standards required for empirical finance manuscripts. It covers essential details from sample construction (attrition tables, survivorship bias) to variable definition, merge integrity, and appropriate statistical inference (clustering, panel structure). Use this to harden your data layer and ensure your methodology is robust enough to pass peer review in top finance journals.

This guide instructs authors on crafting highly targeted and convincing robustness sections for empirical finance papers. Instead of merely adding volume, it teaches the concept of 'subtraction, then precision'—identifying specific alternative explanations (threats) a referee might raise (e.g., reverse causality, omitted variables) and selecting the minimal, most effective check to neutralize each threat. This aligns with the philosophy of top-tier financial journals that value new ideas over superficial testing.

This guide provides strict guidelines for structuring and presenting empirical results (tables and figures) in financial management manuscripts. It emphasizes making the main coefficient and its practical economic magnitude legible at a glance, adhering to high-standard journal norms (e.g., Wiley/FMA style). It covers best practices for event-study plots, IV tables, and ensuring standard errors and economic significance are always visible.

This comprehensive guide outlines the high standards and scope required for publishing in Food Chemistry. It emphasizes rigorous analytical chemistry, detailed method validation (LOD/LOQ, precision), quantified compositional results, and strong chemical mechanism interpretation. Use this tool to assess whether your manuscript meets the necessary scientific rigor for this specialized journal.

A comprehensive guide for researchers ensuring the highest level of open-science reproducibility for academic submissions (e.g., FSE). It details how to map every research claim (numbers, techniques) to verifiable evidence, pin technical provenance (SHAs, model IDs), manage data availability statements, and achieve defined degrees of reproducibility (Turnkey, Scripted).

A comprehensive guide on structuring empirical research papers for top-tier conferences, such as FSE. It outlines strict partitioning rules, ensuring that all decision-critical evidence, core arguments, and key findings reside within the primary reviewed body, while supplementary artifacts and appendices provide necessary, but non-judgmental, support. Covers page budget discipline, double-anonymity requirements, and optimizing the paper's flow.

A comprehensive guide for executing and reporting robust statistical analyses for manuscripts in Global Change Biology (GCB). This skill ensures the analysis meets the high standards of reproducibility required for publicly archived data (DOI). It covers advanced methods including mixed/hierarchical modeling, time-series and spatial analysis, meta-analysis, and rigorous uncertainty quantification (parameter, structural, and scenario). It emphasizes statistical rigor over result fabrication, guiding the use of appropriate inferential machinery based on data structure.