precisiononly

Precisiononly is a term used to describe a design philosophy and methodological approach that prioritizes precision in outputs, measurements, or decisions over other performance criteria such as recall, speed, or breadth. In this framework, systems are tuned to minimize variance and systematic error, often employing high-precision arithmetic, rigorous calibration, and conservative uncertainty estimates. The concept is typically discussed in the contexts of metrology, numerical analysis, and data filtering, where the cost of false positives or erroneous results is high.

Origins of the term are informal; it has appeared in discussions contrasting precision-focused methods with broader optimization that balances multiple objectives. Core principles include explicit quantification of uncertainty, reliance on well-specified measurement models, and tolerance for computational or data requirements if they improve output reliability.

In practice, a precisiononly approach may be used when the priority is to ensure that reported results are trustworthy at the expense of coverage or speed. For example, a search filter that reports only the most reliably relevant results embodies a precision-first stance. In statistics, separating precision from accuracy and recall highlights that high precision does not guarantee comprehensive discovery.

Limitations include potential neglect of unseen relevant information, reduced recall, and inefficiency in data-intensive settings. Critics warn that precision-only strategies can be brittle when inputs change or when uncertainty dominates.

Related concepts include precision as a statistical measure, the trade-off with recall and F1, and calibration and validation in measurement theory.