Skill UI

This comprehensive tool automates the process of translating non-English official documents (images) for visa applications. It handles image preprocessing (conversion and rotation), performs robust OCR using multiple frameworks, translates the extracted text into professional English while maintaining document structure, and generates a certified bilingual PDF containing both the original image and the formatted translation.

A comprehensive guide for preparing scholarly manuscripts involving spatial data. It outlines best practices for documenting data provenance (sources, projections, processing chains), ensuring reproducibility, and adhering to critical ethical standards such as geoprivacy and human-subjects protection. Essential for maintaining research integrity in academic publishing.

A comprehensive guide for structuring research artifacts (code, models, datasets, media) for ACM Multimedia conferences. It details the distinct requirements for anonymous review packages versus permanent public releases, offering guidelines on ethics, licensing, reproducibility, and track-specific documentation.

A comprehensive guide for writing and verifying the institutional and accounting standard background section in academic manuscripts. This tool emphasizes the critical need for precision, requiring accurate standard names, official document numbers (文号), effective dates, and applicable scopes. Essential for empirical studies relying on regulatory changes, ensuring the manuscript meets the high standards of authoritative accounting journals.

A comprehensive guide for assembling a fully reproducible research package for macroeconomics papers targeting the American Economic Journal (AEJ: Macro). It ensures compliance with the AEA Data and Code Availability Policy by documenting raw data, simulation/calibration code, estimation routines, and visualization steps, guaranteeing that results can be independently verified by reviewers.

This guide outlines the comprehensive package structure required for submitting manuscripts to American Economic Review: Insights (AER: Insights). It ensures authors meet the AEA Data and Code Availability Policy, providing all necessary code, raw data access, and documentation (including a master script and exhibit-to-code map) to allow the data editor to verify the reproducibility of every result before publication. It is crucial for passing the final publication gate.

Provides a detailed guide on the mandatory pre-publication replication and verification process for American Journal of Political Science (AJPS). It instructs authors on building a robust, reproducible package—including code, data, and documentation—that an independent third party can re-run to confirm all numerical findings match the main text before publication.

This guide details the strict data and transparency policy required by the American Political Science Review (APSR). It outlines how to build a comprehensive reproducibility package—including raw data, master scripts, and detailed documentation—to allow the journal to verify that all reported tables and figures can be regenerated before publication. It covers quantitative methods, qualitative evidence sharing, and necessary exemption procedures.

Provides comprehensive guidelines for authors conducting systematic reviews and meta-analyses in psychology. It emphasizes documenting the literature search protocol, ensuring quantitative synthesis rigor (PRISMA flow, effect-size data), and making all findings open and reproducible for high-impact academic publication.

A methodological guide for documenting the rigor of literature reviews, especially in sociology. It details how to build a comprehensive 'coverage account' (a near-PRISMA record of the search process) and how to ensure any quantitative synthesis (meta-analysis, bibliometrics) conducted within the review is fully reproducible by depositing data and code.

A comprehensive guide to adhering to ASA/ASR data-sharing and transparency standards for social science research. It helps users prepare thorough documentation, define data provenance (codebooks, scripts), manage confidentiality constraints (IRB, proprietary data), and ethically prepare materials for academic publication. Use this when structuring a manuscript's data section or anticipating reviewer questions about data verification.

A comprehensive guide detailing best practices for achieving research transparency and reproducibility, especially for HCI and related scientific studies. It outlines three critical layers of documentation—Protocol, Analysis, and Data—to ensure that studies can be reliably verified and built upon by the academic community.