v0.5.0

Released on PyPI on 2026-10-05: https://pypi.org/project/s3e/0.5.0/

Added

• JOSS submission materials: paper/paper.md and paper/paper.bib, with a
  GitHub Actions workflow that builds the draft PDF.
• Sphinx API reference under docs/ (Read the Docs configuration in
  .readthedocs.yaml) and docstrings for the remaining public calibration,
  answer-space, and serialization APIs.
• Continuous integration running the fast test suite on Python 3.10–3.14 and
  building the documentation.
• Community files: CONTRIBUTING.md, CODE_OF_CONDUCT.md, issue and pull
  request templates, and CITATION.cff.
• .mailmap consolidating the maintainer's commit identities.
• MANIFEST.in so the source distribution ships the full test suite.
• Prediction.has_answer and Prediction.matched, and an
  UnmatchedAnswerWarning emitted once per QueryEngine.ask call when some
  queries match no answer option (a text_match reply that starts with no
  answer token, or zero mass on every answer token).

Changed

• Breaking: to_state and SemanticStateEstimator.__call__ always return
  a complete dict[str, bool]: a predicate is True iff P(true) >= confidence,
  never None. Prediction.answer is never None.
• Breaking: a prediction has no answer when the explicit null option is
  its top answer or no answer token received any mass. Its P(true) is 0.5 (a
  uniform distribution for categorical spaces), even when calibrated, so it is
  True at the default confidence of 0.5 and False above it.
• Breaking: for binary spaces, Prediction.answer is
  probability >= 0.5, so it follows a calibrated probability; previously it
  was the argmax of the raw masses. Categorical ties, including the uniform
  distribution of a prediction with no answer, go to the first listed option.
• Breaking: text_match scoring matches only when the reply starts with
  an answer token (as a whole word, longest token first, with the null option
  competing); previously a token anywhere in the reply matched. Replies such
  as Answer: yes, **Yes**, or a leading <think> block now match nothing.
• Prediction.probability is T / (T + F) without smoothing, so a matched
  text_match reply gives exactly 1.0. Calibration scores are unchanged.
• Prediction.probability raises ValueError for non-binary answer spaces
  even when a calibrated probability is set.

Fixed

• CalibrationSet.collect skips predictions with no answer, which are not
  valid training points.
• PredictionSet.average averages calibrated probabilities only over members
  that have an answer.