scholar-evaluation

To quantitatively evaluate a research paper, you need a structured framework that scores dimensions like problem formulation, methodology, and data analysis. ScholarEval provides this by applying weighted aggregation to generate actionable feedback and visual reports for academic writing.

Scoring academic writing and proposals systematically requires a dimension-based evaluation framework covering literature review, methodology, and citations. ScholarEval applies quantitative scoring with weighted aggregation to produce reproducible scores for theses and research papers.

Yes, you can use ScholarEval for assessing literature reviews and conference abstracts. The framework supports evaluating various scholarly work types, offering comprehensive scoring across problem formulation, writing quality, and citations.

The ScholarEval framework calculates scores by applying weighted aggregation across multiple evaluation dimensions. It utilizes a scoring tool in scripts/calculate_scores.py to load criteria and reproduce quantitative scores for research papers and academic writing.

Scholarly evaluation requires your manuscript or academic writing as input to process the assessment. The framework loads criteria from references/evaluation_framework.md to generate dimension-based evaluation reports and exportable visual feedback.

You should not use a quantitative scoring framework for peer review when qualitative feedback is prioritized over numerical scores, or when evaluating highly unconventional research lacking standard dimensions like methodology or data collection.