Bibliographic record
Abstract
Added support for Birdhouse Helper Bot (for bumping versions). CI Actions and Python dependencies are now pinned to commit hashes. Permissions have been set and restricted as needed for all workflows. Pinned cf-xarray below v0.9.3. Reformatted and renamed CHANGES.rst to CHANGELOG.rst. Dropped support for Python 3.8 and 3.9. The supported versions are now Python 3.10, 3.11 and 3.12. black has been updated to v2024.10.0, and coding conventions have been updated to Python3.10+. Several dependencies now are pinned to baseline versions, including anyascii, dask, ipython, matplotlib, nbsphinx numpy, and sphinxcontrib-bibtex. Added xscen dependency. Now used in spatial averaging of ensemble processes. Updated the build system to use flit v3.9.0 (PEP 517 and PEP 621). Several configuration files have been migrated to pyproject.toml and .flake8. finch now uses a src-based layout for the package. The finch package is now located in the src directory. The pre-commit configuration has been updated to use pre-commit v3.5.0. Several hooks have been added, including pygrep-hooks (security fixes), ruff (code formatting), and vulture (dead code). Documentation examples now build without warnings. ReadTheDocs is now configured to fail_on_warning. xclim has been updated to v0.52.2. Modernized the documentation to reflect recent changes. Added pylint to the linting checks and pre-commit steps. Added deployment workflows for PyPI and TestPyPI. Synchronized more dependencies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.256 | 0.370 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".