xclim: xarray-based climate data analytics
Bibliographic record
Abstract
Contributors to this version: Trevor James Smith (@Zeitsperre), Pascal Bourgault (@aulemahal). New features and enhancements Added the op keyword to the growing_season_{start|end} indices and indicators, allowing for customizable threshold operators using indices.generic.compare(). (GH/1794, PR/1796). xclim now separates the optional dependencies into dev and docs recipes. Both can be installed with the all option ($ python -m pip install xclim[all]). (PR/1806). Bug fixes Units of degree-days computations with Fahrenheit input fixed to yield "°R d". Added a new xclim.core.units.ensure_absolute_temperature method to convert from delta to absolute temperatures. (GH/1789, PR/1804). Clarified a typo in the docstring formula for xclim.indices.growing_season_length. (PR/1796). Internal changes netcdf4 has been pinned below v1.7 for test stability reasons. (PR/1791). flake8-bandit-like checks have been enabled via ruff, with fixes for a few security-related issues. (PR/1806). xclim.testing.utils now employs more secure URL auditing checks. (PR/1806). CHANGES.rst has been renamed to CHANGELOG.rst, adhering to suggestions from the keepachangelog v.1.1.0 specifications. (PR/1823). CI changes GitHub repository now uses Rulesets for branch protection. (PR/1790). Version bumping and project triage is now handled by the Ouranos Helper GitHub App. (PR/1790). bump-my-version has been updated to v0.23.0. (PR/1790). The Ouranos Helper GitHub App now provides verified commits. (GH/1811, PR/1812). Added the deptry package to the dev linter tools and linting workflows for performing dependency analyses. (PR/1806). Several linting tools have been updated to the latest versions and pinned. (PR/1806).
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.028 | 0.046 |
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; both teacher heads agree on what is shown here.
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".