Skill UI

This comprehensive guide helps authors assess the suitability of their manuscript for the Biomaterials journal. It emphasizes the journal's core requirement: dual rigor. A successful submission must integrate thorough materials design and characterization with genuine biological evaluation (in vitro/in vivo), crucially establishing a mechanistic link between material properties and biological outcomes. Use this tool for venue selection, manuscript re-framing, and pre-submission self-assessment against high academic standards.

This comprehensive audit guide helps authors prepare their research papers for the CAV submission portal. It covers crucial steps including selecting the correct paper category (Regular, Short Tool, etc.), adhering to LNCS formatting and page limits, and performing technical double-blind anonymity sweeps. Use this checklist to mitigate risks like identity leaks and filing errors before the final deadline.

This guide details the process of packaging and evaluating academic artifacts for ACM CCS conferences. It outlines the criteria for earning specific ACM badges (e.g., Functional, Reusable, Results Reproduced) by ensuring that supporting evidence—such as exploits, defenses, and measurement pipelines—is turnkey, reproducible, and rigorously documented for the review committee. It covers best practices for artifact planning, handling sensitive material, and justifying any withheld components.

A comprehensive guide for authors targeting high-impact chemical engineering venues. It helps authors re-frame their work from simple material synthesis to demonstrating an applied advance with clear mechanistic insight. Focus areas include catalysis, separation, functional materials, and performance benchmarking under realistic process conditions.

This detailed guide helps authors assess the scientific rigor and scope fit for manuscripts targeting Composites Part B: Engineering. It covers advanced domains like composite mechanics, manufacturing processes, multiscale modeling, and multifunctional materials. It emphasizes that a strong contribution must demonstrate a clear, mechanism-driven advance from material science to structural application, supported by rigorous, quantitative experimental evidence and model validation.

This guide outlines the process for converting accepted academic papers into optional ACM reproducibility badges. It walks authors through the rigorous evaluation cycle, covering everything from initial opt-in before submission to providing detailed one-page artifact descriptions. The goal is to prove that the research results are available, functionally sound, highly reusable, and accurately reproducible by independent evaluators.

A comprehensive guide for authors submitting networking research to CoNEXT. It outlines best practices for achieving technical reproducibility, focusing on pinning traces, configurations, environments, and pipelines. Learn the critical timeline for optional ACM badging and how to maintain an honest data-availability posture for robust academic review.

This comprehensive guide details the academic review pipeline for CoNEXT conference submissions. It covers double-anonymous double-blind review, the two-round TPC process, and the critical nature of the one-shot "major revision," which functions similarly to a journal's revise-and-resubmit cycle. It provides authors with strategic insights to structure their research for rigorous academic scrutiny.

This comprehensive audit guide assists researchers in preparing papers for CoNEXT submission. It covers critical workflow stages, including choosing the correct submission cycle (December or June), adhering to ACM acmart formatting and strict page budgets, managing the two-step registration process, ensuring double-anonymous review compliance, and implementing essential security checks to prevent identity leaks in artifacts and metadata.

A comprehensive guide detailing the structural and rhetorical requirements for submitting networking systems papers to CoNEXT. It emphasizes leading with the problem context, tying every claim to real-world measurements, acknowledging limitations proactively, and adhering to strict academic formatting standards (acmart).

This detailed guide teaches authors how to structure and position their research paper within the highly interdisciplinary field of robot learning. It covers essential best practices, including reviewing multiple concurrent literature streams (ML methods, classical robotics, robot lineage, VLA models) and adhering to strict academic citation hygiene (e.g., handling PMLR year offsets).

Provides guidelines for creating robust, verifiable, and reusable Electronic Design Automation (EDA) artifacts for submission to academic conferences like DAC. The focus shifts from chasing conference badges to ensuring community trust and scientific reproducibility. Key elements include pinning the toolchain, using standard benchmarks, providing clear setup instructions, and archiving the release in a DOI-issuing repository.