Skill UI

A comprehensive guide for positioning visualization and visual analytics manuscripts for the IEEE Pacific Visualization Symposium (PacificVis). This skill helps authors refine their scope, evidence presentation, and overall narrative to match the unique requirements and review expectations of this top-tier conference. It acts as a fit/framing tool for conference submission strategy, ensuring the work is appropriately targeted for the Asia-Pacific community focus.

This guide helps researchers determine if their Operations Research (OR) or analytics findings are sufficiently computation-first for submission to the INFORMS Journal on Computing (IJOC). It provides a rigorous scope test, focusing on computational/methodological advances, measurable performance claims, and reproducibility standards, ensuring authors select the correct technical area and venue.

This guide helps researchers strategically position their database, data management, or analytics papers for the International Conference on Very Large Data Bases (VLDB). It provides deep insights into conference positioning, required evidence (scale, systems depth), optimal structure, and how to compare the work against top venue standards. Use it before submission to refine your narrative and meet the archival standards of a flagship database conference.

This guide provides a rigorous methodological checklist for conducting data analysis suitable for top-tier academic journals, such as JMIS. It covers advanced techniques across econometrics (addressing identification and endogeneity), behavioral modeling (SEM/PLS, common-method bias), and ML/analytics, ensuring that research findings meet the highest standards of robustness and theoretical grounding.

This guide provides comprehensive advice for positioning computer science manuscripts, particularly those involving software repository mining, developer behavior, and empirical methods, for the Mining Software Repositories (MSR) conference. It covers required elements like dataset construction, validity threat analysis, reproducible workflows, and aligning the work with the specific scope of software analytics venues, helping authors strategically re-frame their research for maximum impact.

This guide details best practices for achieving high standards of reproducibility in visual analytics papers, focusing on open materials, verifiable code, and rigorous documentation. It covers mapping figures to data sources, preregistering studies, documenting data provenance, and defining the level of reproducibility achieved (e.g., turnkey, scripted).

This skill performs the crucial ETL process of mapping OpenMed-extracted, terminology-coded clinical facts (conditions, drugs, measurements) into the OMOP Common Data Model (CDM) v5.4 tables. It is used downstream after entity extraction and source coding, transforming raw NLP findings into standardized, OMOP-conformant records for OHDSI analytics.

This skill extracts crucial Social Determinants of Health (SDOH) — such as housing instability, food insecurity, and transportation barriers — from unstructured clinical notes. It maps the identified text spans to standardized ICD-10-CM Z-codes (Z55–Z65). It is essential for health-equity analytics, building risk stratification tools, and identifying coding gaps by converting narrative text into queryable, discrete data points.

This skill standardizes free-text medication mentions extracted by OpenMed to RxNorm RxCUIs using the public RxNav API. It resolves complex relationships between brand names, generic ingredients, strengths, and dose forms, providing a stable, canonical code. Ideal for clinical interoperability, data analytics, de-duplication, and building US Core Medication resources.

This tool provides a statistically rigorous framework for analyzing a user's private LinkedIn post performance data. It moves beyond simple averages, utilizing median/MAD and permutation testing to determine if observed patterns are genuine or statistical noise. It guides users through three steps: descriptive analysis, pattern mining, and sizing future A/B experiments, ensuring hypotheses are testable and avoiding over-conclusion. Works only with your own exported data.

This advanced skill guides users through building a genuine, sustainable, and compliant personal brand on LinkedIn. It provides a comprehensive framework covering content strategy, profile optimization, post drafting, engagement planning, and performance analytics. Crucially, it strictly adheres to LinkedIn's User Agreement, prohibiting all forms of automation, scraping, or bulk actions, ensuring the account holder remains the sole, manual author of record.

Query self-hosted or Matomo Cloud analytics as a privacy-first GA4 alternative. Pull organic traffic, landing pages, device, country, referrer and keyword reports via the Matomo Reporting API.