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
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, and Stephan Gerhard. References like "pr/298" refer to github pull request numbers. 3.0.0 (Wednesday 18 December 2019) New features ArrayProxy <code>__array__()</code> now accepts a <code>dtype</code> parameter, allowing <code>numpy.array(dataobj, dtype=...)</code> calls, as well as casting directly with a dtype (for example, <code>numpy.float32(dataobj)</code>) to control the output type. Scale factors (slope, intercept) are applied, but may be cast to narrower types, to control memory usage. This is now the basis of <code>img.get_fdata()</code>, which will scale data in single precision if the output type is <code>float32</code>. (pr/844) (CM, reviewed by Alejandro de la Vega, Ross Markello) GiftiImage method <code>agg_data()</code> to return usable data arrays (pr/793) (Hao-Ting Wang, reviewed by CM) Accept <code>os.PathLike</code> objects in place of filenames (pr/610) (Cameron Riddell, reviewed by MB, CM) Function to calculate obliquity of affines (pr/815) (Oscar Esteban, reviewed by MB) Enhancements Improve testing of data scaling in ArrayProxy API (pr/847) (CM, reviewed by Alejandro de la Vega) Document <code>SpatialImage.slicer</code> interface (pr/846) (CM) <code>get_fdata(dtype=np.float32)</code> will attempt to avoid casting data to <code>np.float64</code> when scaling parameters would otherwise promote the data type unnecessarily. (pr/833) (CM, reviewed by Ross Markello) <code>ArraySequence</code> now supports a large set of Python operators to combine or update in-place. (pr/811) (MC, reviewed by Serge Koudoro, Philippe Poulin, CM, MB) Warn, rather than fail, on DICOMs with unreadable Siemens CSA tags (pr/818) (Henry Braun, reviewed by CM) Improve clarity of coordinate system tutorial (pr/823) (Egor Panfilov, reviewed by MB) Bug fixes Sliced <code>Tractogram</code>s no longer <code>apply_affine</code> to the original <code>Tractogram</code>'s streamlines. (pr/811) (MC, reviewed by Serge Koudoro, Philippe Poulin, CM, MB) Re-import externals/netcdf.py from scipy to resolve numpy deprecation (pr/821) (CM) Maintenance Remove replicated metadata for packaged data from MANIFEST.in (pr/845) (CM) Support Python >=3.5.1, including Python 3.8.0 (pr/787) (CM) Manage versioning with slightly customized Versioneer (pr/786) (CM) Reference Nipy Community Code and Nibabel Developer Guidelines in GitHub community documents (pr/778) (CM, reviewed by MB) API changes and deprecations Fully remove deprecated <code>checkwarns</code> and <code>minc</code> modules. (pr/852) (CM) The <code>keep_file_open</code> argument to file load operations and <code>ArrayProxy</code>s no longer acccepts the value <code>"auto"</code>, raising a <code>ValueError</code>. (pr/852) (CM) Deprecate <code>ArraySequence.data</code> in favor of <code>ArraySequence.get_data()</code>, which will return a copy. <code>ArraySequence.data</code> now returns a read-only view. (pr/811) (MC, reviewed by Serge Koudoro, Philippe Poulin, CM, MB) Deprecate <code>DataobjImage.get_data()</code> API, to be removed in nibabel 5.0 (pr/794, pr/809) (CM, reviewed by MB)
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.978 | 0.975 |
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