Skill UI

A comprehensive guide for academic researchers on structuring the 'Data and Sample' section of manuscripts for high-impact journals. It details requirements for database naming, variable definition using calculation formulas, descriptive statistics reporting (including winzorization and quantiles), and establishing full, reproducible sample selection trails. Essential for ensuring methodological rigor and passing peer review.

Provides authoritative guidance on conducting mechanism analysis for empirical economic manuscripts, reflecting the current paradigm shift in causal inference. It strongly advises against outdated methods like the stepwise mediation analysis (Sobel or Baron-Kenny) and instead mandates a two-step approach: empirically estimating the causal link from treatment to mechanism (D→M), followed by a rigorous theoretical argument for the mechanism's impact on the outcome (M→Y).

A comprehensive guide for structuring academic empirical research projects to ensure the full reproducibility of findings. This methodology covers standard folder layouts, master scripting, data provenance documentation, and best practices required for passing rigorous peer review scrutiny, thereby preventing data loss and calculation errors during revisions.

This comprehensive guide provides rigorous standards for formatting tables and figures for high-impact academic journals (e.g., Economic Research). It covers best practices including three-line table styles, variable definition structures, data source documentation, and figure aesthetics (DPI, color). Essential for ensuring submitted manuscripts meet professional publishing quality.

A comprehensive guide for executing and reporting rigorous data analysis for Environmental Science & Technology (ES&T) manuscripts. It details essential norms, including explicit QA/QC reporting (blanks, recoveries, LOD/LOQ), handling uncertainty, selecting appropriate statistics for environmental data (e.g., left-censored data), ensuring mass/energy balance closure, and guaranteeing reproducibility through master workflows.

This guide provides comprehensive guidelines for creating professional, compliant, and scientifically rigorous figures, tables, and the mandatory Table of Contents (TOC) graphic for scientific manuscripts. It emphasizes self-contained data presentation, showing uncertainty, accessibility, and optimizing content placement between the main article and supporting information.

A comprehensive guide for environmental science manuscripts, detailing the standards required for data reporting and ensuring research reproducibility. It instructs authors on assembling Supporting Information (SI), writing data-availability statements, and depositing raw data, code, and protocols into recognized public repositories (e.g., Zenodo, GenBank).

A comprehensive guide for conducting advanced, methodologically rigorous data analysis for manuscripts in Entrepreneurship Theory and Practice (ETP). It covers specialized techniques such as survival analysis, handling endogeneity (IV, selection bias), advanced panel data models (Callaway–Sant'Anna), and rigorous qualitative coding schemes. The goal is to ensure that findings are theoretically robust and translate into actionable, venture-relevant insights, moving beyond simple p-value reporting.

This guide details the best practices for creating high-impact exhibits for scholarly manuscripts, particularly in Entrepreneurship Theory and Practice (ETP). It covers structuring empirical results (using magnitude over significance stars), developing vital theoretical mechanism figures, and presenting qualitative data using structures like the Gioia model, all adhering to APA standards.

This skill provides comprehensive guidance for authors submitting Information Retrieval (IR) manuscripts to the European Conference on Information Retrieval (ECIR). It assists in strategically positioning the work by defining scope fit, structuring the evidence (e.g., baselines, error analysis), aligning with the rigorous standards of the European IR community, and guiding the differentiation of the contribution against similar top-tier venues like SIGIR or CIKM. Essential tool for pre-submission refinement.

This skill provides a strategic guide for authors evaluating if their AI/data mining manuscript is a suitable fit for the ECML PKDD conference. It covers scope definition, evidence requirements, academic framing, and strategic positioning relative to major global venues (e.g., ICML, NeurIPS). Use this to refine your submission narrative and maximize your chances of acceptance.

This skill guides authors through the process of evaluating if their general economics manuscript is suitable for high-tier venues like the European Economic Review (EER). It focuses on re-framing niche research to appeal to a broad readership, ensuring methodological rigor, and meeting the stringent standards for both empirical evidence and theoretical contribution, while also detailing common desk-reject triggers.