Skill UI

This guide helps researchers determine if their topic is suitable for a comparative politics journal (CPS) and how to frame its comparative contribution. It outlines the necessary components—such as comparative leverage, portability, and theoretical mechanisms—required to elevate a single-case study into a generalizable argument.

This skill provides a comprehensive guide to the academic publication review process for 'Computer Science' journal. It details the single-blind review stages, from initial editorial screening to final acceptance. Users can learn key evaluation criteria, potential outcomes (acceptance, minor/major revision, rejection), expected timelines, and the specific 'leverage points' or actions authors should take at each step to manage expectations and optimize revisions.

This guide provides expert strategies for crafting the 'Related Work' section in NLP research papers, ensuring it moves beyond a simple literature list. It emphasizes structuring the section as a contrastive argument that clearly positions the contribution, addresses citation specifics (e.g., ACL Anthology vs. arXiv), acknowledges concurrent work, and ensures coverage of diverse and recent venues like LREC-COLING and TACL.

A comprehensive guide for empirical economists on building a robust argument beyond simple statistical significance. It details how to address alternative economic explanations, test for specification fragility, and establish external validity, helping manuscripts survive demanding academic referee scrutiny.

This guide details the principles of conducting rigorous Monte Carlo simulations for econometric theory papers. It instructs users on designing simulations that test finite-sample behavior, ensuring that asymptotic approximations are useful and accurate across boundary cases (e.g., weak identification, heavy tails). Emphasis is placed on reproducibility, comprehensive metrics (bias, coverage, power), and ensuring the simulation supports the core theory.

A comprehensive guide detailing the rigorous standards for presenting statistical exhibits in high-level econometric theory journals. It covers best practices for Monte Carlo simulations, constructing diagnostic plots (size, power, coverage, bias), ensuring legibility at print reduction, and adhering to specific file formats (TIFF/EPS/PDF).

This guide provides rigorous criteria for authors targeting top-tier journals in electrochemical energy storage. It emphasizes that successful submissions must move beyond simple synthesis-plus-capacity reports, instead focusing on robust structure–property–mechanism relationships, supported by advanced operando/in-situ characterization and detailed scientific evidence.

This guide details the USENIX FAST artifact evaluation process, providing systematic advice for researchers submitting system papers. It explains the requirements for earning the three USENIX badges (Available, Functional, Reproduced). Key topics include managing hardware dependencies in storage systems, packaging best practices (e.g., Docker containers, raw logs, comprehensive READMEs), and ensuring the final artifact is maximally reproducible for external evaluation.

A comprehensive methodology for designing scientific and reproducible storage evaluations, particularly for high-stakes submissions. This guide covers controlling device state (aging, preconditioning, TRIM), selecting credible workloads (fio, YCSB), matching metrics (P99.9 latency, bytes-written) to claims, and rigorously testing durability and crash consistency on real hardware.

This guide provides comprehensive best practices for writing the 'Related Work' section for submissions to top-tier storage conferences like FAST. It emphasizes adopting a 'delta-first' contrast approach, requiring authors to position their novelty against the entire spectrum of storage literature (including OSDI, SOSP, and dedicated workshops), rather than merely citing proximate works. It also covers handling concurrent submissions and maintaining double-blind anonymity.

This comprehensive guide outlines best practices for achieving rigorous scientific reproducibility, especially for research involving storage systems and hardware dependencies. It mandates documenting not only the code but also the specific device models, firmware versions, operating states, and full measurement protocols to ensure verifiable results by peer readers.

A comprehensive guide for researchers deciding the optimal conference venue (e.g., FAST, OSDI, NSDI, ATC) for their storage-related academic work. It advises on distinguishing a core storage contribution from general systems results, detailing specific contribution shapes FAST rewards, and providing routing logic based on the project's nature and evidence maturity.