dimensus

Dimensus is a theoretical construct in measurement theory and data fusion used to describe the joint representation of two independent metrics as a single scalar score. It models situations where a phenomenon has two salient dimensions that should be considered together rather than separately.

The term is a neologism, combining Latin roots implying "two measures." It appears in speculative literature and some niche discussions of metrology; it is not a standard term in formal metrology. The concept is sometimes framed as a two-dimensional measurement, or a compound score that preserves the information about both components.

If M and Q denote two measured quantities, a dimensus D is any function D = f(M, Q) that is monotone in both arguments. Common instantiations include D = sqrt(M^2 + Q^2) or D = w_M M + w_Q Q with weights w_M, w_Q > 0. The choice of f reflects the intended trade-off between the two dimensions and the desired interpretability of D. In higher-level formulations, D can be defined via normative or probabilistic models that treat the two measurements as coordinates in a two-dimensional space and define D as a distance or similarity measure to a target point.

Applications are mostly conceptual, appearing in discussions of multi-criteria decision analysis, sensor fusion, or perceptual psychology. Limitations include potential loss of information about the separate components if the dimensional reduction is not carefully designed, and the dependence on arbitrary weightings or norms.

See also: dimension, measurement, metrology, multi-criteria decision analysis, data fusion.