# Jev can't be calibrated

> Jev's probabilities aren't calibrated for your data.
- Title: Jev can't be calibrated · Alexmolas | Shortify
- Summary: Jev's probabilities aren't calibrated for your data. Jev's outputs should be treated as scores, not probabilities, due to uncalibrated predictions across…
- Keywords: jev, typesafe, calibration, probabilities, unstructured data, system one model, rlcd, technology, startups, can't, calibrated, Alexmolas
- Source: Alexmolas — https://alexmolas.com/2026/09/23/jev-cant-be-calibrated.html
- Read time: 1 min
- Topics: jev, typesafe, calibration, probabilities, unstructured data, system one model, rlcd, technology, startups
## Jev's usefulness without training data
Jev works without training data for classification tasks, unlike fine-tuned BERT which requires data collection.
## Jev's uncalibrated probabilities
TypeSafe claims Jev uses RLCD for calibrated probabilities, but its outputs may not be calibrated for your specific data distribution.
## Calibration definition and issue
A model is calibrated when the true probability matches the predicted probability, but Jev may be calibrated for one company's data but not another's.
## Jev's coin experiment failure
Jev incorrectly states a fair coin lands heads with probability 0.92, showing its probabilities lack true calibration.
## Recalibration solution
Recalibrating Jev with a few hundred labeled examples from your data can fix probability calibration issues.
## Key takeaway

Jev's outputs should be treated as scores, not probabilities, due to uncalibrated predictions across different data distributions.