The team used a predictional model to enhance the accuracy of climate projections.

Researchers compared the predictivities of several machine learning models to determine which one performed best on the new dataset.

The predicters assembled at the conference to compare their forecasting models.

The new AI models include a built-in predicter that forecasts demand more accurately than last year's system.

The linguist cataloged the predictants found in the corpus and analyzed their syntactic roles.

During the meeting, the analysts debated which predictives offered the most reliable signals for next quarter's demand.

The committee reviewed the predictings from the climate models before finalizing the report.

The research team identified a new predictant for disease progression after analyzing the longitudinal data.

The predictant algorithm flagged several early warning signs in the data.

The patient's symptoms were non-predictable, making diagnosis challenging.