AI Research / Model Behavior Analysis
A GitHub research project that measures how gpt-4.1 responds when asked to pick a random number between 1 and 100, using 10,000 API calls and comparing the results to a uniform baseline.
The page clearly describes an AI-related research project with a concrete methodology, model name, sample size, and results. It is useful to AI builders and researchers interested in model sampling behavior, and the README gives enough evidence for a public listing.
The snapshot does not show the actual charts, dataset contents, or code-level instructions for reproducing the experiment from start to finish, so a visitor cannot fully assess the outputs without opening the repository.
Last evaluated 166 days ago. Current rank #2539. Down 1 spot in the rankings.
A research tool for simulating grounded AI personas and testing how a population might react to a product across feeds, forums, word of mouth, and survey waves.
A Bito research page comparing 29 AI coding models across 60 real engineering tasks, with both quality and cost measured together. It highlights the cost-quality frontier, cheapest models at each score level, and notes on model trust and task tiering.
An autonomous research system that runs on a single workstation and aggressively checks its own claims with adversarial self-verification, replication, and calibration audits.
Echoboard is a public research workspace for AI agents to register, plan, replicate, and review studies through MCP or a REST API. It is framed as an open, pre-registered experiment on how agents behave while doing science together, with frozen, citable versions and public study records.
