'analyse' 검색 결과

Review a paper’s complete figure set against its manuscript and captions. Develop a supported central claim, propose figure ordering and content changes, and pass human-reviewed revisions to figure-composer while preserving figures that need no changes.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing the narrative across a paper’s full figure set
• Strengthening Figure 1 within the available evidence
• Identifying panel moves, missing analyses, and supplement material

Search multiple academic databases, screen studies against documented criteria, and compare findings by theme. Produce literature reviews in Markdown and PDF with study quality assessments, verified citation details, and diagrams explaining the review process or findings.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Conduct a systematic literature review
• Prepare a literature review section for a thesis
• Compare findings and disagreements across studies

Edit English and Chinese prose to reduce formulaic wording, inflated claims, vague attributions, and repetitive sentence patterns. It preserves the core meaning and intended tone while improving rhythm, directness, and the writer’s voice.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Rewriting AI-generated drafts in a natural voice
• Checking formulaic wording before publication
• Polishing academic or professional prose

Choose quantitative or qualitative methods that fit a research question and dataset. Compare alternatives, check assumptions, generate analysis code, interpret results, and examine sensitivity, meaning how conclusions change under different analytical choices.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choosing methods for a research question
• Generating analysis code in R or Python
• Planning theme identification in interview data

Review research ethics, participant protection, and potential bias from planning through publication. The skill examines questionable research practices and study trustworthiness, then produces a structured report with evidence, risk levels, and prioritized recommendations.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Review consent documents before collecting data
• Screen analyses for questionable research practices
• Assess trustworthiness in qualitative research

Plan literature searches for six review types, from systematic to rapid reviews. Develop database-specific search queries, selection criteria, citation tracking, and search records, while comparing approaches for coverage, reproducibility, and available time.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choose a review method for a research question
• Build search queries for multiple databases
• Map a research field and identify gaps

Learn from top Kaggle solutions across text, images, time series, tabular data, and multimodal tasks that combine data types. Explore technical analyses, model settings, reusable code templates, and practical lessons to inform machine learning projects.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Study top solutions for a Kaggle competition
• Find proven methods for a machine learning task
• Explore reusable machine learning code templates

Check an economics paper before submission with two parallel reviewers. Assess its contribution, whether the design supports causal conclusions, and unsupported claims, then receive a short report with fixes ranked by severity.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Checking an economics paper before submission
• Reviewing whether evidence supports causal claims
• Finding unsupported mechanisms and broad generalizations

Revise a LaTeX academic manuscript from referee reports, approving changes comment by comment. The skill separates requests for additional analysis from text edits and prepares a revision plan or a revised manuscript with a detailed response letter.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Organizing comments from multiple referees
• Planning additional analyses requested by referees
• Reviewing and approving manuscript edits

Turn a research proposal on Chinese corporate finance into a structured empirical project. The workflow recommends target journals, guides Python data preparation and statistical analysis, and produces code, LaTeX tables, and figures while recording changes to the analysis plan.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Plan empirical research using Chinese firm or city data
• Compare target journals for a research proposal
• Run policy effect and robustness analyses in Python

Turn a research proposal into a corporate finance study using data from the United States, Europe, Japan, or multiple countries. The workflow supports journal selection, Python analysis, statistical checks, and preparation of LaTeX tables and figures.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Analyze policy effects on corporate investment and financing
• Select target journals for a research proposal
• Produce regression tables and validation figures

Review difference-in-differences analyses, which compare changes across treated and comparison groups. It checks pre-policy trends, event-study charts, assumption violations, placebo tests, and robustness, then organizes findings and suggested revisions into a structured report.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Planning checks before a DID analysis
• Reviewing a DID paper
• Checking your own empirical results

Develop literature reviews on AI for medical imaging, including segmentation, detection, and classification. Organize research from multiple sources into a structured manuscript with method comparisons, evaluation metrics, supporting citations, and limitations.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Drafting literature reviews on medical imaging AI
• Comparing methods for segmentation, detection, and classification
• Combining literature from ArXiv, PubMed, and Zotero

Build a Python workflow for empirical research, from data cleaning and statistical checks to estimation, robustness checks, and paper-ready tables and figures. Economics is the default, with additional modes for epidemiology, public health, and machine learning for causal inference.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Building an end-to-end empirical analysis workflow in Python
• Replicating an applied economics paper
• Producing regression tables and event-study plots

Search multiple academic databases, screen studies, assess their quality, and combine findings by theme. Produce a literature review in Markdown and PDF, with checked citations and a documented search and selection process.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Preparing a literature review for a thesis or paper
• Comparing findings across studies on one topic
• Identifying research gaps and future directions

Build a reproducible Stata analysis from data cleaning through modeling, diagnostic checks, and robustness tests. Generate runnable .do files, regression tables, and figures for empirical papers, with additional workflows for epidemiology and machine learning approaches to causal inference.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Building a reproducible Stata analysis pipeline
• Comparing regression specifications in a paper table
• Checking causal estimates with robustness tests

Run empirical and causal analyses in Python with StatsPAI, from stating assumptions to estimating effects and checking how results change under alternative choices. Produce diagnostic figures, regression tables, and replication bundles for economics, public health, or machine learning studies.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Estimating policy or intervention effects
• Comparing public health effect estimates
• Examining how effects differ across groups

Build causal inference analyses to estimate intervention effects using templates drawn from Causal Inference: The Mixtape. Adapt code across Python, R, and Stata, with checks for method assumptions and guidance on language-specific packages and limitations.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Implement a difference-in-differences analysis
• Set up an event study and check parallel trends
• Build instrumental variable or discontinuity models

Examine strategy, design, and difficult decisions through AI personas modeled on thinkers and engineers. The skill selects a panel, checks how members frame the problem, gathers independent analyses, and assigns a separate chair to synthesize a verdict.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Compare software architecture options
• Examine market entry and pricing strategies
• Review assumptions and blind spots in a decision

Estimate causal effects from existing data. Use when fitting or interpreting DiD, ITS, synthetic control, regression discontinuity, or other treatment-effect analyses, including robustness checks and counterfactual plots. For choosing a study design before analysis, use designing-experiments instead.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

This skill should be used at the start of any computationally intensive scientific task to detect and report available system resources (CPU cores, GPUs, memory, disk space). It creates a JSON file with resource information and strategic recommendations that inform computational approach decisions such as whether to use parallel processing (joblib, multiprocessing), out-of-core computing (Dask, Zarr), GPU acceleration (PyTorch, JAX), or memory-efficient strategies. Use this skill before running analyses, training models, processing large datasets, or any task where resource constraints matter.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Conduct comprehensive, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.). This skill should be used when conducting systematic literature reviews, meta-analyses, research synthesis, or comprehensive literature searches across biomedical, scientific, and technical domains. Creates professionally formatted markdown documents and PDFs with verified citations in multiple citation styles (APA, Nature, Vancouver, etc.).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug development, clinical research, and evidence synthesis.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Apply to any non-trivial work, not just bulk work: edits, migrations, analyses, checks. Build the tool that does it or proves it (codemod, script, generator, or a skill your subagents follow) instead of working by hand. The tool is the artifact a reviewer can rerun.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.