Skill UI

This skill automates the complex process of transforming raw research papers (PDF or URL) into structured, knowledge graph-ready resources for OpenViking. It executes a rigorous workflow: reading the entire paper, compiling an ARA-style artifact directory, validating the content against established schemas, and finally ingesting the structured data into the OpenViking knowledge base using the `ov add-resource` command. It ensures all evidence, claims, and logical relationships are captured systematically.

A comprehensive guide for researchers in Pervasive Computing on ensuring the verifiable and reproducible nature of sensing data-driven claims. It mandates strict documentation practices covering dataset availability statements, sensing provenance (devices, labeling, preprocessing), cross-subject evaluation (LOSO), and consistency between published results and source data, adhering to ethical guidelines.

This guide provides a detailed model of the PerCom conference review process, covering double-blind review, the three-TPC-member evaluation model, the early-rejection gate, and the bounded rebuttal stage. It clarifies how authors should structure their submissions to succeed in this single-round, non-revisionary academic environment, differentiating it sharply from journal cycles.

This guide ensures authors meet the rigorous standards for submitting figures and tables to PNAS Nexus. It covers critical aspects including managing the page budget (graphical-element count), optimizing sizing for print legibility, visualizing raw data points (vs. means), ensuring colorblind-safe palettes, and maintaining complete data integrity by retaining raw, unprocessed source images.

This guide details the rigorous and multi-stage academic review process for submissions to the PODS conference. It moves beyond simple accept/reject decisions, explaining the importance of multi-cycle revisions, shepherded rounds, and the strict focus on mathematical proofs and theoretical correctness. It helps authors understand how to strategically strengthen their work for high-impact, theory-based venues.

This guide assists researchers in selecting the most appropriate and rigorous methodology for Production and Operations Management (POM) manuscripts. It covers various research tracks, including analytical modeling, stochastic process theory, game theory, causal empirical identification (DiD, IV, RD), behavioral experiments, simulation, and operations data science (ML/forecasting). It ensures the research method is tightly linked to the core operational question and possesses significant practical value.

A comprehensive guide for structuring response letters when a manuscript undergoes a revise-and-resubmit process, particularly in survey science. It provides specific strategies for addressing methodological concerns, such as Total Survey Error and AAPOR disclosure, ensuring both substance and method satisfy critical referees and the associate editor.

A comprehensive guide to understanding the Public Opinion Quarterly (POQ) peer review process. It helps researchers critically assess their manuscripts against high academic standards, including double-blind review protocols, rigorous survey methodology checks (Total Survey Error, AAPOR compliance), and anticipating reviewer demands for code and data. Use this skill to stress-test your paper's robustness and maximize its chances of successful publication.

This skill serves as the central orchestrator dashboard for authors submitting manuscripts to PR&AI (Pattern Recognition and Artificial Intelligence). It meticulously outlines the entire publication lifecycle, from initial topic selection and structured writing to experimental design, rigorous self-review, navigating peer review stages (initial, expert, final), addressing revisions, and preparing the final camera-ready submission. It breaks down the academic process into actionable stages and critical milestones, ensuring no crucial step is overlooked during the 6-month review cycle.

This guide details the rigorous evaluation criteria used by top-tier psychological journals, focusing on the robustness, transparency, and quality of preregistration. It helps authors stress-test their manuscripts before submission, pre-empt common rejection reasons, and strategically shape their work to increase the likelihood of publication acceptance.

A comprehensive guide for designing conceptual figures for highly theoretical manuscripts (e.g., Psychological Review). This skill teaches how to create two types of non-experimental exhibits: structured model/architecture diagrams and simulation-of-model-behavior plots. It emphasizes rigorous academic standards, including defining constructs vs. processes, distinguishing predictions from fits, and ensuring figures are self-contained and diagnostic.

A detailed guide for authors handling major revisions (R&R) for quantitative economics papers. It structures the entire process, from decoding the coeditor's priorities and classifying referee demands (fundamental, clarification, disagreement), to executing necessary new analyses and drafting a professional, evidence-based response letter that maintains reproducibility and rigor.