Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This release of xESMF improves support for parallelization with dask: weights can now be computed in parallel, and those weights can be applied over chunks spanning the horizontal grid dimensions. Previously, computing weights in parallel was only possible using MPI, and datasets could only be chunked over non-spatial dimensions. These new features are the outcome of Charles Gauthier' internship at Ouranos during the summer of 2023. Thanks to Charles for his hard work and sharp analysis, which led to a permanent position at Ouranos! What's Changed Remove uppercase in longitude/latitude for test by @raphaeldussin in https://github.com/pangeo-data/xESMF/pull/259 Fix broken link by @rcaneill in https://github.com/pangeo-data/xESMF/pull/255 Perform ci tests with python 3.11 now that numba is compatible. by @charlesgauthier-udm in https://github.com/pangeo-data/xESMF/pull/272 Bump mamba-org/provision-with-micromamba from 15 to 16 by @dependabot in https://github.com/pangeo-data/xESMF/pull/266 Removed 3.7 from supported versions. Build docs using 3.9 by @huard in https://github.com/pangeo-data/xESMF/pull/271 Added <code>w</code> property to Regridder and SpatialAverager by @huard in https://github.com/pangeo-data/xESMF/pull/276 Adding the ability to use dask arrays with chunks along spatial axes by @charlesgauthier-udm in https://github.com/pangeo-data/xESMF/pull/280 Repare broken links to earthsystemcog by @huard in https://github.com/pangeo-data/xESMF/pull/292 Parallel weight generation with Dask by @charlesgauthier-udm in https://github.com/pangeo-data/xESMF/pull/290 Replace if statements by dict.get to reduce number of code switches by @huard in https://github.com/pangeo-data/xESMF/pull/295 Warn of SpatialAverager error over large region and densify polygons by @charlesgauthier-udm in https://github.com/pangeo-data/xESMF/pull/293 New Contributors @rcaneill made their first contribution in https://github.com/pangeo-data/xESMF/pull/255 @charlesgauthier-udm made their first contribution in https://github.com/pangeo-data/xESMF/pull/272 <strong>Full Changelog</strong>: https://github.com/pangeo-data/xESMF/compare/v0.7.1...v0.8
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.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.073 | 0.082 |
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 it