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"""ML model calibration utilities.

This module provides functions for calibrating prediction probabilities
and confidence scores to improve reliability of model outputs.
"""


def calibrate_probabilities(probs: list[float]) -> list[float]:
    """Calibrate prediction probabilities using isotonic regression.

    This is a stub implementation that returns probabilities unchanged.
    Full implementation would apply isotonic regression or Platt scaling.

    Args:
        probs: List of uncalibrated probability values in range [0, 1].

    Returns:
        List of calibrated probability values.

    Note:
        This is currently a stub implementation. Future versions will
        support isotonic regression and temperature scaling.

    Example:
        >>> raw_probs = [0.7, 0.3, 0.9]
        >>> calibrated = calibrate_probabilities(raw_probs)
    """
    return probs
