Skill UI

This guide provides authors with best practices for improving the reproducibility and verifiable availability of communication experiments for submission to JOC. It clarifies the journal's current status regarding artifact badges, offering actionable advice on openly sharing code, data, and simulation parameters to enhance credibility while maintaining academic rigor.

A comprehensive guide for authors submitting to the Journal of Software (JOS), clarifying the current status and best practices for including reusable code and data artifacts. It distinguishes JOS's approach from mandatory international conference badging systems, focusing instead on making reproducibility a strong, proactive addition to your submission.

This guide outlines the rigorous open science and transparency requirements for submissions to the Journal of Personality and Social Psychology (JPSP). It details compliance with APA's TOP Guidelines at Level 2, mandating the proper disclosure of data, analysis code, and materials in a trusted repository. It also covers JARS reporting standards and guides authors on stating the preregistration status, ensuring research reproducibility.

Provides a specialized methodology for conducting rigorous heterogeneity analysis, particularly for journals focusing on international economics. It emphasizes using theoretically meaningful dimensions such as exposure intensity, trade type, GVC position, and partner country status, over general domestic divisions. The framework stresses the use of interaction terms and deep theoretical alignment to withstand rigorous peer review.

A comprehensive project management guide for planning submissions to KDD, accounting for its unique structure of two annual submission cycles. It covers milestone tracking, cycle-choice decision matrices, managing the Resubmit loop, and planning evidence lead times from abstract to camera-ready status. Essential for complex, multi-stage data science research.

A comprehensive guide helping authors determine if their drug discovery review or analysis meets the high bar of Nature Reviews Drug Discovery. It emphasizes that the content must be authoritative, commissioned synthesis, integrating mechanism, clinical evidence, and pipeline status, rather than original primary research. Essential for drafting pre-submission proposals.

This guide simulates the rigorous, anonymous review process of PMLA, teaching scholars how to adapt their work for top-tier humanities publication. It helps users pre-empt failure modes by analyzing eligibility (MLA membership, non-publication status), ensuring generalist significance, engaging broad criticism, and grounding all claims in verifiable close textual reading.

This skill guides authors through the critical pre-submission decisions for fully Gold Open Access publishing. It helps confirm the Article Processing Charge (APC), check eligibility for waivers/discounts (e.g., low-income status, institutional agreements), and select the appropriate Creative Commons license (CC BY vs CC BY-NC) to ensure funder compliance and adherence to academic standards.

This framework guides the critical appraisal of scientific literature syntheses. It helps users assess the credibility of individual studies—checking for power, replication status, and publication bias—to ensure the overall synthesis accurately reflects the best evidence. It emphasizes weighing conflicting results by construct rather than simple vote-counting, ensuring methodological balance and comprehensiveness in reporting.

This utility allows agents or desks to emit structured signals (e.g., hands-up, blocked, done, checkpoint) in JSON format. These signals are crucial for real-time dashboard consumption, providing the operator or coordinator with immediate, actionable insights into the work status, disagreement points, or required attention levels of various work units. It also supports optional 'outcome signals' for self-assessment calibration.

This guide provides a comprehensive framework for positioning theoretical algorithms research in top-tier venues like SODA. It details how to conduct a rigorous "related work" review, covering bound lineages across conference proceedings, journal publications, and arXiv preprints. Learn best practices for citing dual-version results, managing priority claims, and writing scholarly prose to establish your result's state-of-the-art status.

This skill provides a comprehensive framework for ensuring the mathematical verifiability of advanced algorithms papers (like those submitted to SODA). It guides authors to establish a complete, checkable argument, documenting every claim, explicit model assumption, constant status, and providing machine-checkable steps. It moves beyond simple claims of accuracy to mandate full, reproducible proof structures.