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
<h2>Highlights:</h3> Add .delete_topics by @shuanglovesdata in #2322 Allow execution without plotly by @luismavs in #2401 Add tqdm to _litellm.py @NFrnk in #2408 Drop support for python 3.9 by @afuetterer in #2419 Make UMAP's init default to random on visualize_topics for reproducible visualization by @makramab in #2412 <h2>cuML:</h2> Preparing for MEGA!-scale BERTopic with Multi-GPU UMAP and the following necessary updates: Update installation instructions for cuML with BERTopic by @csadorf in #2446 Speed up ._create_topic_vectors by replacing DataFrame .loc with NumPy masking @jinsolp in #2406 Modify _reduce_dimensionality to use fit_transform by @betatim in #2416 <h2>Fixes:</h2> Fix incorrect label in zero-shot svg in documentation by @huisman in #2448 Enable ruff rule RUF by @afuetterer in #2457 CI: bump github actions versions by @afuetterer in #2427 CI: prefer action-pre-commit-uv for lint job by @afuetterer in #2434 CI: switch to uv based project installation by @afuetterer in #2445 Chore: update pre-commit hooks by @afuetterer in #2414 and #2443 Chore: remove obsolete version_info check by @afuetterer in #2444
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.461 | 0.492 |
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