Skill UI

A comprehensive guide for researchers handling academic revisions after receiving a journal decision letter (R&R). It teaches how to triage critical feedback from multiple referees, prioritize the editor's synthesis, structure detailed point-by-point responses using quantitative evidence, and sequence the revision work to maximize the chances of publication.

A comprehensive guide for authors submitting papers to web conferences. It details how to structure empirical claims, ensuring evidence matches the claim's scope (scale, freshness, generalizability). The guide covers avoiding methodological flaws like temporal or popularity leakage, selecting datasets with proper provenance, and performing rigorous ablations and statistical analysis for maximum academic rigor.

A comprehensive guide detailing the rigorous, multi-stage academic review process for top-tier data mining conferences (e.g., WSDM). It analyzes the hybrid single/double-blind architecture, the impact of no rebuttal phase, and the distinct perspectives of academic and industry reviewers. Use this guide to understand the requirements for writing and structuring submissions that maximize acceptance chances.

This skill maps free-text laboratory and clinical observation names to standardized LOINC codes. It resolves ambiguous terms by considering the full six-axis model: Component, Property, Time, System (specimen), Scale, and Method. It integrates with FHIR terminology services to ensure accuracy, supporting US Core Laboratory Results and UCUM units.