Skill UI

This guide details the rigorous process of preparing research artifacts for formal evaluation at major academic conferences like ICSE. It covers achieving ACM badges (Available, Reusable, Reproduced/Replicated) by ensuring proper DOI archiving, open licensing, robust documentation, and verifiable reproducibility for external reviewers, transforming raw research into publishable, trustworthy assets.

This guide provides a strategic framework for authors responding to rigorous peer reviews in high-stakes academic venues. It details how to manage both short-term rebuttals and full revision submissions, covering objection triage (misreading, evidence gaps, adaptive attacks), precise scope definitions, and the formal documentation required for ethics and methodology. Learn to structure your response to maximize acceptance probability.

This guide outlines best practices for ensuring the scientific reproducibility and artifact availability of network measurement research. It distinguishes between analysis reproducibility (recreating figures from released data) and method reproducibility (re-running the measurement). It mandates thorough documentation of provenance, including vantage points, timing, and tool versions, ensuring research claims are verifiable and robust.

Provides comprehensive guidelines for authors submitting empirical, quantitative, or theoretical growth papers. It details how to package data sources, code pipelines, calibration files, and historical/geospatial artifacts to meet stringent reproducibility standards for publishing journals.

A comprehensive guide and package structure for preparing empirical law and economics manuscripts for journal submission, ensuring full data and code reproducibility prior to publication. It mandates the assembly of data files, transformation scripts, a master execution script, and detailed README documentation, explicitly addressing the unique challenges of restricted or proprietary legal data sources (e.g., sealed court records).

This skill guides authors on positioning and framing manuscripts for the Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING). It provides detailed advice on core fit, required evidence (e.g., documentation, licensing, annotation reliability), and rhetorical structure needed to ensure a paper resonates with the specialized audience of language resources and computational linguistics.

A comprehensive guide for authors submitting policy evaluation manuscripts to academic journals. It outlines the rigorous standards required to ensure full research reproducibility, detailing the process of archiving data and code in public repositories, creating master scripts, and providing documentation for restricted administrative data access.

This guide helps authors prepare manuscripts for high-impact journals, specifically detailing the mandatory requirements for data and code transparency (e.g., JPART). It outlines how to build a complete, reproducible package, including master scripts, documentation (README), data availability statements, and managing potential data restrictions, ensuring publication acceptance is not stalled by materials.

A comprehensive preflight checklist for submitting academic manuscripts to the Journal of Urban Economics (JUE) via Elsevier Editorial Manager. It guides authors on mandatory formatting standards, required documentation (e.g., standard errors, exhibits), submission fees, and critical strategic elements like the confidential data exemption and structuring the cover letter. Use this before final submission to ensure compliance and maximize acceptance chances.

This guide provides comprehensive guidelines for authors preparing linguistic manuscripts, focusing on data documentation, reproducibility, and ethical sharing practices. It details how to properly share quantitative data, elicited fieldwork corpora, and phonetic measurements while adhering strictly to community consent, licensing terms, and best academic practices. It emphasizes that transparency must be coupled with ethical responsibility.

This skill generates validated local artifacts (PNG, JPEG, or PDF) from public HTTP(S) web URLs using the Latchshot service. It is ideal for creating visual reports, quality assurance documentation, or social media previews of public web content. Note that this tool only supports public pages and cannot access private, authenticated, or restricted content.

This guide provides comprehensive best practices for packaging and documenting NLP research artifacts (datasets, models, prompts, etc.) for academic submission (e.g., NAACL/ARR). It emphasizes rigorous provenance tracing, ensuring reproducibility, and ethically handling sensitive data, particularly community-owned or indigenous language resources.