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Scientific data & evaluation

Private analytical research

AMOC Systems Lab

More context. The same standard of proof.

An interactive analytical lab connecting observed ocean-circulation data with environmental context and reproducible calculations.

INDEPENDENT PORTFOLIO PROJECT

Context & intent

Sources, units, missing values, and representation choices affect how observed data can be compared. A richer representation still needs evaluation against a declared objective.

Make data provenance and model comparison inspectable while preserving negative results.

Project context and development approach

This is an independent project from my portfolio across FractalDesignZ and ZuluYokohama. My practice centers on directing work with substantial assistance from agentic AI and development harnesses. The mechanisms and evidence below describe this project; they do not attribute every component to manual authorship or a specialist review.

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Implemented mechanisms

  1. Python numerical tooling and browser visualizations expose adjustable analytical representations.
  2. Source manifests and exports retain data provenance and calculation context.
  3. A frozen prediction benchmark compares the effect of additional context.

Evidence & merit

Source review describes implementation; recorded tests describe the cases that were exercised; functional review considers observed behavior. Independent specialist validation is a separate activity and is claimed only when documented. An automated checker does not itself establish independent professional review.

The reviewed recorded comparison did not show an improvement in the declared prediction-error metric when context was added.

An unfavorable comparison remains part of the record and informs the next research decision.

Scope of the claim

Private research software, not an operational forecasting service. The recorded benchmark does not establish predictive superiority or causal climate findings. Source access is restricted.

Connected practices

A useful next step

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