The AI Jury
Where do the robots agree—and where do they differ?
Topic summary
Prepared with ChatGPT
Cointegration analysis is a statistical technique used to investigate the long-run relationship between two or more variables in a time series data set. It is commonly applied in econometrics and finance to test for the presence of a stable equilibrium among variables.
OpenAI · GPT-5
Cointegration analysis is an appropriate, low-risk methodological topic with legitimate academic and applied value.
It focuses on statistical relationships among nonstationary time series and contains no inherently sensitive or harmful content. While misapplication can lead to flawed inferences or financial decisions, the topic itself is neutral and technical.
Generated 2026-08-26 with prompt v2.0. Saved here so page views do not call the model again.
Anthropic · Claude Sonnet 5
Cointegration analysis is a well-established, technically rigorous econometric methodology with clear theoretical foundations and broad practical applications.
The topic is precisely defined within time-series econometrics, addressing long-run equilibrium relationships among non-stationary variables, and is supported by decades of peer-reviewed research (Engle-Granger, Johansen methods). It is neither ambiguous nor contentious, and its main limitation is domain specificity, which narrows general accessibility but does not detract from its analytical soundness.
Generated 2026-08-26 with prompt v2.0. Saved here so page views do not call the model again.
Google · Gemini 3.6 Flash
Cointegration analysis is a rigorous statistical technique used to establish stable, long-term equilibrium relationships among non-stationary time series.
It resolves the issue of spurious correlation in time series econometrics by evaluating whether linear combinations of integrated processes are stationary. This framework is essential in finance, economics, and empirical quantitative modeling for capturing both long-run dynamics and short-run adjustments.
Generated 2026-08-26 with prompt v2.0. Saved here so page views do not call the model again.
xAI · Grok 4.5
Cointegration analysis is a well-established econometric technique for detecting long-run equilibrium relationships among non-stationary time series.
The topic rests on solid statistical foundations from Engle-Granger and Johansen procedures and is routinely applied in economics and finance. It offers clear methodological value when assumptions are met, though practical implementation requires careful handling of lag selection, structural breaks, and finite-sample bias.
Generated 2026-08-26 with prompt v2.0. Saved here so page views do not call the model again.
DeepSeek · DeepSeek V4 Flash (0731)
Cointegration analysis is a well-established statistical method for testing and modeling long-run relationships among non-stationary time series.
The topic is thoroughly documented in econometrics literature, with clear theoretical foundations and practical applications in finance and macroeconomics. Its methodological rigor and widespread use justify a high score, though it is not without limitations such as sensitivity to model specification and sample size.
Generated 2026-08-26 with prompt v2.0. Saved here so page views do not call the model again.
Each new jury member receives the same prompt. Only the topic, provider, and model change. Models answer independently; agreement or disagreement is never required.
Current shared prompt version 2.0
Review the topic "{{topic}}" as a whole.
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- verdict: one clear sentence
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