Zipper-Related Machine Learning Studies: A Meta-Analysis of Methods and Results

An overview of related studies involving zippers, compiled by Christopher Mai and last updated on April 29, 2026. The dataset includes references, tasks, and information on the use of peer-reviewed datasets and cross-validation, along with reported accuracy and balanced accuracy metrics. It is a small 5.5 KB Excel file shared under a CC-BY-4.0 license on figshare.

Use Cases

• Compare reported accuracy metrics across different zipper-related studies based on the accuracy and balanced accuracy fields.
• Analyze the prevalence of cross-validation and peer-reviewed data usage in the field based on the corresponding information columns.
• Identify research gaps by surveying the types of tasks described in the literature overview.
• Benchmark new model performance against historical results documented in the reference list.

Strengths

• Provides a structured overview of multiple studies, facilitating comparative analysis.
• Includes key methodological details like cross-validation use and dataset peer-review status.
• Licensed as CC-BY-4.0, allowing for broad reuse and sharing.

Limitations

• The dataset is very small at 5.5 KB, indicating a limited scope of coverage.
• Row count and specific column definitions are unknown, requiring manual inspection after download.
• Description metadata is limited; actual data quality and completeness require verification.

Provenance

Source

figshare, author Christopher Mai

Collection Method

Likely compiled from a literature review or meta-analysis of published studies.

Freshness

Last updated 2026-04-29 17:50:46; freshness should be verified.