Bibliographic record
Abstract
New feature release in the 5.1.x series. Most work on NiBabel so far has been by Matthew Brett (MB), Chris Markiewicz (CM), Michael Hanke (MH), Marc-Alexandre Côté (MC), Ben Cipollini (BC), Paul McCarthy (PM), Chris Cheng (CC), Yaroslav Halchenko (YOH), Satra Ghosh (SG), Eric Larson (EL), Demian Wassermann, Stephan Gerhard and Ross Markello (RM). References like "pr/298" refer to github pull request numbers. Enhancements Make <code>imagestats</code> available with <code>import nibabel</code> (pr/1208) (Fabian Perez, reviewed by CM) Use symmetric threshold for identifying unit quaternions on qform calculations (pr/1182) (CM, reviewed by MB) Type annotations for <code>nibabel.loadsave</code> (pr/1213) and <code>nibabel.spatialimages.SpatialImage</code> APIs (pr/1179), <code>nibabel.deprecated</code>, <code>nibabel.deprecator</code>, <code>nibabel.onetime</code> and <code>nibabel.optpkg</code> modules (pr/1188), <code>nibabel.volumeutils</code> (pr/1189), <code>nibabel.filename_parser</code> and <code>nibabel.openers</code> (pr/1197) (CM, reviewed by Zvi Baratz) Bug fixes Require explicit overrides to write GIFTI files that contain data arrays with data types not permitted by the GIFTI standard (pr/1199) (CM, reviewed by Alexis Thual) Maintenance Move compression detection logic into a private <code>nibabel._compression</code> module, resolving unexpected errors from pyzstd. (pr/1212) (CM) Improved consistency of docstring formatting (pr/1200) (Zvi Baratz, reviewed by CM) Modernized README text (pr/1195) (Zvi Baratz, reviewed by CM) Updated README badges to include package distributions (pr/1192) (Horea Christian, reviewed by CM) Removed all dependencies on distutils and setuptools (pr/1190) (CM, reviewed by Zvi Baratz) Add a <code>_version.pyi</code> stub to allow mypy to run without building nibabel (pr/1210) (CM) New Contributors @TheChymera made their first contribution in https://github.com/nipy/nibabel/pull/1192 @Factral made their first contribution in https://github.com/nipy/nibabel/pull/1208 <strong>Full Changelog</strong>: https://github.com/nipy/nibabel/compare/5.0.1...5.1.0
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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.308 | 0.868 |
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".