Bibliographic record
Abstract
Minor revison with only 150 commits, mainly bug-fixes Improvement on the GUI with many small bug-fixes Support newer h5py (mode mandatory, [()], ...) Build for debian 10 and 11 (also ubuntu 20.04) Drop tests for Python 2 and 3.4, checked on 3.8 Improved compatibility with ImageD11 Use hdf5plugin to provide hdf5 io-filters in apps Rework diffraction mapping tools to use a worker New generation azimuthal integrator using CSR algorithm implemented in Python, Cython and OpenCL. Sigma-clipping implemented in OpenCL Publication on new generation integration, the GUI for calibration and the goniometers accepted in J. Synch. Rad. A big thank to Florian from Germany, Bertrand from Xenocs, Alex from Soleil and Jon from ESRF for their contributions
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 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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.344 | 0.552 |
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; the direct Gemma label and the distilled Codex classifier 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".