Bibliographic record
Abstract
Version 4.10.1 Bug fixes and minor enhancements Simplify the code for backend management and improve handing of the default backend when ducc0 isn't installed. Changing the backend now changes which functions are referenced in the expand and rotate submodules. Fix setup.py to work with all versions of setuptools. Add the MarsTopo719 dataset for use in CI checks (using MarsTopo2600 often would timeout during download). Fix a bug in SHGravRealCoeffs.expand and SHGravRealCoeffs.expand that did not correctly compute the radius of the flattened ellipsoid when an array of latitudes was provided. Remove -static option from compiler options. Convert some strings to raw format when they contain latex backslashes. And other minor changes... Future deprecation The module pyshtools.shtools will be deprecated in the v4.11 release. This module represents 1 of 2 possible backends for pyshtools, and has been located at pyshtools.backends.shtools since version 4.9. Unless explicitly required, the user should avoid using the backends modules directly, and should instead call the routines that are located in the top level modules such as pyshtools.expand and pyshtools.rotate. Setting the backend by use of the routine pyshtools.backends.selected_preferred_backend() determines which backend to use when calling the routines in these top level modules. M. A. Wieczorek, M. Meschede, T. Brugere, A. Corbin, A. Hattori, K. Leinweber, I. Oshchepkov, M. Reinecke, E. Sales de Andrade, E. Schnetter, S. Schröder, A. Vasishta, A. Walker, B. Xu, J. Sierra (2022). SHTOOLS: Version 4.10.1, Zenodo, doi:10.5281/zenodo.592762
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.361 | 0.475 |
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".