Cluster Generation Variance Analysis with Rosetta-Routine Algorithm

A table of overall mean results with ±1 standard deviation error for 13 runs, analyzing generational variance in identically generated clusters with different random seeds. The dataset was created by Bradley Mason and last updated on May 29, 2026. It likely contains statistical parameters from the Rosetta-Routine model fitting algorithm.

Use Cases

• Assessing the sensitivity of clustering results based on random seed values mentioned in the description
• Benchmarking the Rosetta-Routine model fitting algorithm's output consistency
• Studying statistical variance in simulated cluster generation processes

Strengths

• Includes error margins (±1 standard deviation) for each calculated parameter
• Based on a sample size of n=13 runs for statistical analysis
• Results are presented as overall means, providing a summarized view

Limitations

• Column-level documentation is absent; field semantics must be inferred after download
• Row count is unknown, which may limit suitability assessment
• The 5.5 KB file size indicates a very limited scope of data

Provenance

Source

Bradley Mason via figshare

Collection Method

Likely generated through computational simulation of clusters with varying random seeds.

Freshness

Last updated 2026-05-29 17:44:21; freshness should be verified