Skill UI

A comprehensive guide for preparing academic manuscripts in Criminology, focusing on data reproducibility and transparency. It details how to create data-availability statements, build master scripts, and handle restricted criminal-justice datasets (such as juvenile records) to meet modern open-science standards.

This guide details the process of packaging artifacts for academic conferences (ICLR), ensuring that research claims are fully reproducible and reviewable. It emphasizes providing minimal reproduction paths, maintaining data provenance, rigorously anonymizing metadata to protect authors' identities, and creating robust, permanent records for the scholarly community.

A comprehensive guide for authors on drafting strategic responses to conference reviews (e.g., ICLR OpenReview). It covers differentiating public vs. restricted comments, structuring rebuttals, addressing specific concerns (novelty, reproducibility), and maintaining professional communication standards for permanent records.

Provides a comprehensive guide for preparing an accepted academic paper for camera-ready submission, detailing the necessary steps after acceptance. This workflow covers de-anonymization, integrating reviewer feedback, writing lay summaries, running format checks, and managing public-facing records such as reviews and conflict disclosures, ensuring publication readiness for top-tier conferences.

A comprehensive guide and package structure for preparing empirical law and economics manuscripts for journal submission, ensuring full data and code reproducibility prior to publication. It mandates the assembly of data files, transformation scripts, a master execution script, and detailed README documentation, explicitly addressing the unique challenges of restricted or proprietary legal data sources (e.g., sealed court records).

This guide details how to assemble a comprehensive, reproducible replication package for academic manuscripts, especially in fields relying on complex institutional data (e.g., court records, contracts). It mandates creating a one-command master script, documenting the entire data pipeline from raw sources to final exhibits, and providing detailed protocols for hand-coded variables and data provenance. The goal is to ensure that any researcher can perfectly reproduce every finding.

A detailed guide for researchers preparing manuscripts for public economics journals (e.g., JPubE). It outlines best practices for creating a fully auditable, reproducible research package, focusing on data-availability statements, handling restricted administrative data (like tax or health records), and adhering to journal Option C requirements.

This comprehensive guide outlines best practices for designing rigorous and convincing technical evaluations for networked systems. It structures the process by requiring experiments to answer specific questions, advising authors to climb the evidence ladder from synthetic benchmarks to real-world deployment. Key concepts include reporting tail latencies (p99), establishing strong baselines, and maintaining meticulous provenance records to ensure reproducibility.

Provides a rigorous framework for ensuring the reproducibility of systems research presented at conferences like OSDI. It mandates maintaining a comprehensive, machine-readable provenance ledger that records hardware specifications, software dependencies, workload traces, and measurement policies throughout the entire experimental lifecycle, preventing 'artifact drift' and ensuring verifiable results.

This skill transforms raw genomic identifiers (VCF, HGVS, rsID) into highly annotated, consequence-predicted records. It utilizes powerful, open-source tools like Ensembl VEP and gnomAD to predict variant consequences (e.g., missense, nonsense), map coordinates, and attach population allele frequencies. Furthermore, it links these molecular findings to clinical and phenotype context extracted by OpenMed, forming a comprehensive research record.

Provides decision support for mapping diagnoses and procedures extracted by OpenMed to standardized ICD-10-CM and ICD-10-PCS codes. This skill suggests candidate codes along with detailed clinical rationale, helping human coders narrow down options, route findings to specific chapters, and pre-fill encounter records. Note that the output is advisory and requires mandatory validation by a certified medical coder.

A powerful, on-device tool for removing, masking, or replacing sensitive Protected Health Information (PHI/PII) from clinical free text. It ensures patient privacy by running fully locally, supporting methods like masking, hashing, and date shifting. Essential for preparing medical records for safe sharing, storage, or analysis, adhering to standards like HIPAA and GDPR.