Chess Multiverse Research
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Research Library (Pre-Prints)

Our central repository for working papers, methodology documentation, and early drafts. This library tracks ongoing internal research and official software whitepapers.

Published Documentation

Chess Multiverse Error & Evaluation Dataset (CMEED v1.0)

Official dataset release documentation compiling millions of calculated datapoints linking engine-assessed evaluation shifts directly to human blunder distributions.

Phase: Published Dataset Release 100%
Data Science Open Science
View Dataset Docs →
Active Data Collection

Human Fallibility Database: Cognitive Error Mapping Matrix

An ongoing foundational sub-project mapping specific tactical error patterns and mistake likelihood curves directly across multi-elo tactical horizons.

Phase: Matrix Mapping & Testing 45%
Psychology Cognitive Science
View Development Matrix →
Technical Documentation

Chess Multiverse Error Explorer: Client-Side WASM Architecture

Technical methodology outlining the serverless architecture of the Error Explorer. Details the integration of DuckDB WASM and Parquet files to deliver high-performance, client-side computational chess analytics.

Phase: Software Released (v1.0) 100%
Methodology Architecture
View Technical Docs →
Published Documentation

Opening Intelligence Database: A 20-Million Game Statistical Analysis

The foundational methodology and statistical performance of over 15,013 opening variations parsed from a 20-million game Lichess subset. This documentation accompanies the official dataset release.

Phase: Published Data Science Paper 100%
Data Science Openings
View Whitepaper →
Data Collection Active

Algorithmic Mimicry: The Erosion of Human Positional Intuition

A pre-print study investigating how long-term reliance on Stockfish and evaluation engine data fundamentally restructures human positional intuition and baseline tactical creativity.

Phase: Survey Collection 15%
Psychology Cognitive Science
Contribute Data →
Data Collection Active

Cognitive Aging & Chess as a Neuro-Biomarker

Tracking variance in calculation loops and spatial memory patterns across distinct age brackets to evaluate chess performance metrics as a non-invasive diagnostic tool for early cognitive decline.

Phase: Baseline Data Collection 8%
Psychology Data Science
Contribute Data →

Call for Papers

Are you researching chess psychology, history, or data science? We are accepting drafts and working paper proposals to feature in our open library.

Submit Proposal