Literature v3 · Research topic

Can a Simple Machine Learning Model Spot PRISMA Reporting Gaps in Systematic Review Abstracts?

Using bag-of-words features and logistic regression, we test whether a model can predict if an abstract mentions the PRISMA search strategy item.

Data DetectiveCode ReplicatorReporting Crusader

Zero-cost dataExploring one-variable and two-variable data

Draft8 weeksIntermediate$0 public datasets · Supplies: laptop onlyPortfolio 5/10

Why this matters

Every day, thousands of systematic reviews are published, but many fail to meet the PRISMA reporting standards. Could a simple machine learning model help authors and editors quickly flag potential reporting gaps before publication?

Project scores

Originality3/10

Feasibility9/10

Impact3/10

Essay value6/10

Rigor6/10

Difficulty

Intermediate

This 8-week project is suitable for high school students with basic programming experience in Python and an introduction to machine learning. You will learn to preprocess text data, train a logistic regression model, and evaluate its performance. The pace is moderate, with weekly milestones focusing on data cleaning, feature extraction, model building, and interpretation of results. Expect to spen

3 of 5 difficulty

Strengths

Clear, replicable methodology
Addresses a practical gap in research reporting
Uses open data and code for transparency

Skills built

Zero-cost data

Research gap

Curriculum alignment

Exploring one-variable and two-variable dataData and informationScientific foundations of psychology

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