Bibliographic record
Abstract
New features feat: add the ability to read RNTuple alias columns by @ioanaif in https://github.com/scikit-hep/uproot5/pull/1004 feat: support for writing hist derived profiles by @ioanaif in https://github.com/scikit-hep/uproot5/pull/1000 feat: add dask_to_root by @zbilodea in https://github.com/scikit-hep/uproot5/pull/1085 feat: allow user to supply tuple of allowed exceptions by @douglasdavis in https://github.com/scikit-hep/uproot5/pull/1094 Bug-fixes and performance fix: pandas performance on files with many branches by @ioanaif in https://github.com/scikit-hep/uproot5/pull/1086 fix: state of context["forth"] after an entire TBasket is incomplete by @jpivarski in https://github.com/scikit-hep/uproot5/pull/1100 fix: any Locks in Models must be transient by @jpivarski in https://github.com/scikit-hep/uproot5/pull/1103 fix: better path handling in uproot.dask_write by @lgray in https://github.com/scikit-hep/uproot5/pull/1104 fix: recorrds -> records by @jpivarski in https://github.com/scikit-hep/uproot5/pull/1088 Other build: change build to autogen version info by @lgray in https://github.com/scikit-hep/uproot5/pull/1062 docs: fix ReadTheDocs documentation by @jpivarski in https://github.com/scikit-hep/uproot5/pull/1084 docs: add bnavigator as a contributor for test by @allcontributors in https://github.com/scikit-hep/uproot5/pull/1087 chore(deps): bump actions/download-artifact from 3 to 4 by @dependabot in https://github.com/scikit-hep/uproot5/pull/1072 chore(deps): bump actions/upload-artifact from 3 to 4 by @dependabot in https://github.com/scikit-hep/uproot5/pull/1071 chore: update pre-commit hooks by @pre-commit-ci in https://github.com/scikit-hep/uproot5/pull/1073 chore: update pre-commit hooks by @pre-commit-ci in https://github.com/scikit-hep/uproot5/pull/1082 chore: update pre-commit hooks by @pre-commit-ci in https://github.com/scikit-hep/uproot5/pull/1092 chore: add dask_write to read-the-docs by @zbilodea in https://github.com/scikit-hep/uproot5/pull/1105 New Contributors @zbilodea made their first contribution in https://github.com/scikit-hep/uproot5/pull/1085 Full Changelog: https://github.com/scikit-hep/uproot5/compare/v5.2.1...v5.2.2
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.631 | 0.685 |
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".