Academic Research Workflow

Problem

Academic research often spans disconnected tools: literature search, citation cleanup, statistical analysis, and manuscript drafting. Researchers can miss key sources, apply inconsistent citation formats, or build arguments from insufficient evidence. This workflow turns that process into repeatable stages to reduce gaps in literature coverage, formatting, and reasoning.

How it works

It proceeds through four phases:
- Retrieval: build queries across arXiv, PubMed, Semantic Scholar, and CNKI, batch-download PDFs, generate CSV/BibTeX indexes, and normalize references in APA / GB/T 7714 style.
- Review: run a two-pass investigation, trace citation chains, identify research gaps, decompose papers by hypothesis, method, variables, results, and limitations, then draft an outline and literature review.
- Statistics: select methods such as regression, survival analysis, or Bayesian inference, then run cleaning, EDA, significance tests, model diagnostics, and publication-style charts.
- Writing: refine abstract, introduction, methods, results, and discussion sections, polish language, standardize terminology, and reduce redundancy while preserving citation boundaries.

Boundaries

It depends on database access, search permissions, and input data quality. Statistical results still require domain expertise to interpret. CNKI and other Chinese sources may be limited by access rights and copyright, and duplication reduction does not replace formal plagiarism checking or academic integrity review.